{"id":236,"date":"2017-10-05T08:59:38","date_gmt":"2017-10-05T06:59:38","guid":{"rendered":"https:\/\/www.hsu-hh.de\/mathstat\/?page_id=236"},"modified":"2026-04-13T07:51:25","modified_gmt":"2026-04-13T05:51:25","slug":"publikationen","status":"publish","type":"page","link":"https:\/\/www.hsu-hh.de\/mathstat\/forschung\/publikationen","title":{"rendered":"Publikationen &amp; Vortr\u00e4ge"},"content":{"rendered":"\n<ul class=\"wp-block-list\">\n<li><a href=\"#books\" rel='nofollow'>B\u00fccher<\/a><\/li>\n\n\n\n<li><a href=\"#articles\" rel='nofollow'>Artikel<\/a><\/li>\n\n\n\n<li><a href=\"#talks\" rel='nofollow'>Vortr\u00e4ge<\/a><\/li>\n<\/ul>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"books\">B\u00fccher<\/h2>\n\n\n\n<div class=\"wp-block-hsu-publicationblock\"><div class=\"img-area download-image\"><img decoding=\"async\" src=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2024\/03\/Entropy_DTS-100x100.jpg\" alt=\"\" \/><\/div><div class=\"content-area\"><strong>Wei\u00df, C.H. (Ed.):<br>Discrete-Valued Time Series.<\/strong><br>Special Issue Reprint, Entropy, <a href=\"https:\/\/www.mdpi.com\/books\/reprint\/8933-discrete-valued-time-series\" rel='nofollow'>MDPI<\/a>, Basel, 2024.<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-hsu-publicationblock\"><div class=\"img-area download-image\"><img decoding=\"async\" src=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/11\/9781119096962_mittel-100x100.png\" alt=\"\" \/><\/div><div class=\"content-area\"><strong>Wei\u00df, C.H.:<br>An Introduction to Discrete-Valued Time Series.<\/strong><br><a href=\"http:\/\/eu.wiley.com\/WileyCDA\/WileyTitle\/productCd-1119096960.html\" rel='nofollow'>John Wiley &amp; Sons, Inc<\/a>, Chichester, 2018.<br>(<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/forschung\/monographien\/\">Weitere Informationen &#8230;<\/a>)<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-hsu-publicationblock\"><div class=\"img-area download-image\"><img decoding=\"async\" src=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/11\/MathematicaWL_klein-100x100.jpg\" alt=\"Mathematica und Wolfram Language: Einf\u00fchrung - Funktionsumfang - Praxisbeispiele\" \/><\/div><div class=\"content-area\">Wei\u00df, C.H.:<br><strong>Mathematica und Wolfram Language<\/strong><br>Einf\u00fchrung &#8211; Funktionsumfang &#8211; Praxisbeispiele.<br><a href=\"https:\/\/www.degruyter.com\/view\/product\/455762\" rel='nofollow'>De Gruyter Oldenbourg<\/a> Verlag, Berlin, 2017.<br>(<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/forschung\/monographien\/\">Weitere Informationen&#8230;<\/a>)<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-hsu-publicationblock\"><div class=\"img-area download-image\"><img decoding=\"async\" src=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Handbuch9-100x100.jpg\" alt=\"Handbuch Mathematica\" \/><\/div><div class=\"content-area\"><strong>Wei\u00df, C.H.:<br>Mathematica und Wolfram Language &#8211; Eine Einf\u00fchrung.<\/strong><br><a href=\"http:\/\/www.rrzn.uni-hannover.de\/buch.html?&amp;no_cache=1&amp;titel=mathe\" rel='nofollow'>RRZN Handbuch<\/a>, 9., vollst\u00e4ndig \u00fcberarbeitete Auflage, Hannover, 2016.<br>(1. Auflage: 2007, 2. Auflage: 2008, 3. und 4. Auflage: 2010, 5.-7. Auflage: 2011, 8. Auflage: 2013)<br>(<a href=\"http:\/\/www.rrzn.uni-hannover.de\/buch.html?&amp;no_cache=1&amp;titel=mathe\" rel='nofollow'>Weitere Informationen&#8230;<\/a>)<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-hsu-publicationblock\"><div class=\"img-area download-image\"><img decoding=\"async\" src=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Dissertation_mittel-100x100.jpg\" alt=\"Dissertation\" \/><\/div><div class=\"content-area\"><strong>Wei\u00df, C.H.:<br>Categorical Time Series Analysis and Applications in<br>Statistical Quality Control.<\/strong><br>Dissertation (Fakult\u00e4t f\u00fcr Mathematik und Informatik der Universit\u00e4t W\u00fcrzburg), <a href=\"http:\/\/www.dissertation.de\/buch.php3?buch=5926\" rel='nofollow'>dissertation.de &#8211; Verlag<\/a>, Berlin, 2009.<br>(<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/weiss\/dissertation\/\">Weitere Informationen&#8230;<\/a>)<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-hsu-publicationblock\"><div class=\"img-area download-image\"><img decoding=\"async\" src=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Handbuch5-100x100.jpg\" alt=\"Handbuch Statistica\" \/><\/div><div class=\"content-area\"><strong>Wei\u00df, C.H.:<br>STATISTICA &#8211; Eine Einf\u00fchrung.<\/strong><br><a href=\"http:\/\/www.rrzn.uni-hannover.de\/buch.html?&amp;no_cache=1&amp;titel=statistica\" rel='nofollow'>RRZN Handbuch<\/a>, 3., aktualisierte Auflage, Hannover, 2009.<br>(1. Auflage: 2005, 2. Auflage: 2006)<br>(<a href=\"http:\/\/www.rrzn.uni-hannover.de\/buch.html?&amp;no_cache=1&amp;titel=statistica\" rel='nofollow'>Weitere Informationen&#8230;<\/a>)<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-hsu-publicationblock\"><div class=\"img-area download-image\"><img decoding=\"async\" src=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/11\/Mathematica_klein-100x100.jpg\" alt=\"Mathematica kompakt: Einf\u00fchrung - Funktionsumfang - Praxisbeispiele\" \/><\/div><div class=\"content-area\">Wei\u00df, C.H.:<br><strong>Mathematica kompakt<\/strong><br>Einf\u00fchrung &#8211; Funktionsumfang &#8211; Praxisbeispiele.<br><a href=\"http:\/\/www.degruyter.com\/view\/product\/216294?rskey=NE2vE2&amp;result=10\" rel='nofollow'>R. Oldenbourg Verlag<\/a>, M\u00fcnchen, Wien, 2008.<br>(<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/forschung\/monographien\/\">Weitere Informationen&#8230;<\/a>)<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-hsu-publicationblock\"><div class=\"img-area download-image\"><img decoding=\"async\" src=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/11\/Titelbild-100x100.jpg\" alt=\"Datenanalyse und Modellierung mit STATISTICA\" \/><\/div><div class=\"content-area\"><strong>Wei\u00df, C.H.:<br>Datenanalyse und Modellierung mit STATISTICA.<\/strong><br><a href=\"http:\/\/www.degruyter.com\/view\/product\/227220?rskey=NE2vE2&amp;result=8\" rel='nofollow'>R. Oldenbourg Verlag<\/a>, M\u00fcnchen, Wien, 2006.<br>(<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/forschung\/monographien\/\">Weitere Informationen&#8230;<\/a>)<\/div><\/div>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"articles\">Artikel<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">2026<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong><strong>Wei\u00df &amp; Ad\u00e4mmer (2026)<\/strong><br><\/strong>Wei\u00df, C.H., Ad\u00e4mmer, P.: Nonparametric Testing of Spatial Dependence in 2D and 3D Random Fields.<br><a href=\"https:\/\/pubs.aip.org\/aip\/cha\/issue\/36\/4\" rel='nofollow'>Chaos: An Interdisciplinary Journal of Nonlinear Science<\/a> 36(4), <a href=\"https:\/\/doi.org\/10.1063\/5.0307955\" rel='nofollow'>043116<\/a>, 2026.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2026)<\/strong><br>Wei\u00df, C.H., Zhu, F., Kim, H.-Y.: Tobit INARMA models for count time series with negative autocorrelation.<br><a href=\"https:\/\/link.springer.com\/journal\/11749\/volumes-and-issues\/35-1\" rel='nofollow'>TEST<\/a> 35(1), 117-156, 2026.<\/li>\n\n\n\n<li><strong><strong>Silbernagel &amp; Wei\u00df (2026b)<\/strong><br><\/strong>Silbernagel, A., Wei\u00df, C.H.: The Joint Asymptotic Distribution of Entropy and Complexity.<br><a href=\"https:\/\/pubs.aip.org\/aip\/cha\/issue\/36\/2\" rel='nofollow'>Chaos: An Interdisciplinary Journal of Nonlinear Science<\/a> 36(2), <a href=\"https:\/\/doi.org\/10.1063\/5.0308221\" rel='nofollow'>023145<\/a>, 2026.<\/li>\n\n\n\n<li><strong><strong>Silbernagel &amp; Wei\u00df (2026a)<\/strong><br><\/strong>Silbernagel, A., Wei\u00df, C.H.: The autocorrelation structure of integer-valued autoregressive random fields.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/statistics-and-probability-letters\/vol\/233\/suppl\/C\" rel='nofollow'>Statistics &amp; Probability Letters<\/a> 233, 110681, 2026.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2025<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Wei\u00df (2025d)<\/strong><br>Wei\u00df, C.H.: Pgf-based Goodness-of-Fit Tests for Binomial Counts.<br>Accepted for publication in <a href=\"https:\/\/link.springer.com\/journal\/184\/online-first\" rel='nofollow'>Metrika<\/a>, 2025.<\/li>\n\n\n\n<li><strong>Jahn &amp; Wei\u00df (2025)<\/strong><br>Jahn, M., Wei\u00df, C.H.: Modeling multivariate ordinal time series.<br>Accepted for publication in <a href=\"https:\/\/www.tandfonline.com\/action\/showAxaArticles?journalCode=cjas20\" rel='nofollow'>Journal of Applied Statistics<\/a>, 2025.<\/li>\n\n\n\n<li><strong>Ad\u00e4mmer et al. (2025)<\/strong><br>Ad\u00e4mmer, P., Wittenberg, P., Wei\u00df, C.H., Testik, M.C.: Nonparametric Monitoring of Spatial Dependence.<br>Accepted for publication in <a href=\"https:\/\/www.tandfonline.com\/journals\/utch20\" rel='nofollow'>Technometrics<\/a>, 2025.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Kim (2025)<\/strong><br>Wei\u00df, C.H., Kim, H.-Y.: Non-parametric Entropy Tests for Spatial Dependence.<br><a href=\"https:\/\/link.springer.com\/journal\/180\/volumes-and-issues\/40-9\" rel='nofollow'>Computational Statistics<\/a> 40(9), pp. 5315-5352, 2025.<\/li>\n\n\n\n<li><strong>Wei\u00df (2025c)<\/strong><br>Wei\u00df, C.H.: Testing for Dependence by Using Ordinal Patterns: Survey and Perspectives.<br>In Steland et al. (eds.): <a href=\"https:\/\/link.springer.com\/book\/9783031960147\" rel='nofollow'>Stochastic Models, Statistics and Their Applications (SMSA 2024)<\/a>, Springer Proceedings in Mathematics &amp; Statistics, Volume 499, Springer International Publishing, pp. 173-181, 2025.<\/li>\n\n\n\n<li><strong>Jahn (2025)<\/strong><br>Jahn, M.: Discrete-Valued Time Series and Recurrent Neural Network Response Functions.<br>In Steland et al. (eds.): <a href=\"https:\/\/link.springer.com\/book\/9783031960147\" rel='nofollow'>Stochastic Models, Statistics and Their Applications (SMSA 2024)<\/a>, Springer Proceedings in Mathematics &amp; Statistics, Volume 499, Springer International Publishing, pp. 151-159, 2025.<\/li>\n\n\n\n<li><strong>Faymonville et al. (2025)<\/strong><br>Faymonville, M., Jentsch, C., Wei\u00df, C.H.: Semi-parametric goodness-of-fit testing for INAR models.<br><a href=\"https:\/\/projecteuclid.org\/journals\/bernoulli\/volume-31\/issue-4\" rel='nofollow'>Bernoulli<\/a> 31(4), 3213-3234, 2025.<\/li>\n\n\n\n<li><strong>Wei\u00df (2025b)<\/strong><br>Wei\u00df, C.H.: Stein EWMA Control Charts for Count Processes.<br><a href=\"https:\/\/www.routledge.com\/Statistical-Methods-and-Applications-in-Systems-Assurance-and-Quality\/Bersimis-Economou-Rakitzis\/p\/book\/9781032664040\" rel='nofollow'>Methods and Applications in Systems Assurance &amp; Quality<\/a>, Book Series &#8222;Advanced Research in Reliability and System Assurance&#8220;, CRC Press, pp. 3-17, 2025 (<a href=\"https:\/\/arxiv.org\/abs\/2401.11789\" rel='nofollow'>arXiv preprint<\/a>).<\/li>\n\n\n\n<li><strong>Wang et al. (2025)<\/strong><br>Wang, H., Wei\u00df, C.H., Zhang, M.: Goodness-of-fit Testing in Bivariate Count Time Series based on a Bivariate Dispersion Index.<br><a href=\"https:\/\/link.springer.com\/journal\/10182\/volumes-and-issues\/109-2\" rel='nofollow'>AStA Advances in Statistical Analysis<\/a> 109(2), 241-279, 2025.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Swidan (2025c)<\/strong><br>Wei\u00df, C.H., Swidan, O.: Hidden-Markov Models for Ordinal Time Series.<br><a href=\"https:\/\/link.springer.com\/journal\/10182\/volumes-and-issues\/109-2\" rel='nofollow'>AStA Advances in Statistical Analysis<\/a> 109(2), 217-239, 2025.<\/li>\n\n\n\n<li><strong>Silbernagel et al. (2025)<\/strong><br>Silbernagel, A., Wei\u00df, C.H., Schnurr, A.: Non-parametric tests for cross-dependence based on multivariate extensions of ordinal patterns.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/computational-statistics-and-data-analysis\/vol\/210\/suppl\/C\" rel='nofollow'>Computational Statistics and Data Analysis<\/a> 210, 108189, 2025.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Swidan (2025b)<\/strong><br>Wei\u00df, C.H., Swidan, O.: Soft-clipping Autoregressive Models for Ordinal Time Series.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/15264025\/2025\/41\/3\" rel='nofollow'>Applied Stochastic Models in Business and Industry<\/a> 41(3), e70015, 2025.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Zhu (2025b)<\/strong><br>Wei\u00df, C.H., Zhu, F.: Mean-preserving Rounding Integer-valued ARMA Models.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/14679892\/2025\/46\/3\" rel='nofollow'>Journal of Time Series Analysis<\/a> 46(3), 530-551, 2025.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Swidan (2025a)<\/strong><br>Wei\u00df, C.H., Swidan, O.: Weighted Discrete ARMA Models for Categorical Time Series.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/14679892\/2025\/46\/3\" rel='nofollow'>Journal of Time Series Analysis<\/a> 46(3), 505-529, 2025.<\/li>\n\n\n\n<li><strong>Iooss &amp; Wei\u00df (2025)<\/strong><br>Iooss, B., Wei\u00df, C.H.: The ENBIS-23 Quality and Reliability Engineering International Special Issue.<br>Editorial, <a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/10991638\/2025\/41\/3\" rel='nofollow'>Quality and Reliability Engineering International<\/a> 41(3), 917-918, 2025.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Zhu (2025a)<\/strong><br>Wei\u00df, C.H., Zhu, F.: Tobit Models for Count Time Series.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/14679469\/2025\/52\/1\" rel='nofollow'>Scandinavian Journal of Statistics<\/a> 52(1), 381-415, 2025.<\/li>\n\n\n\n<li><strong>Wei\u00df (2025a)<\/strong><br>Wei\u00df, C.H.: The Mollified (Discrete) Uniform Distribution and its Applications.<br><a href=\"https:\/\/wires.onlinelibrary.wiley.com\/toc\/19390068\/2025\/17\/1\" rel='nofollow'>WIREs Computational Statistics<\/a> 17(1), e70016, 2025.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2024<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Yang et al. (2024)<\/strong><br>Yang, K., Zhao, X., Dong, X., Wei\u00df, C.H.: Self-exciting hysteretic binomial autoregressive processes.<br><a href=\"https:\/\/link.springer.com\/journal\/362\/volumes-and-issues\/65-3\" rel='nofollow'>Statistical Papers<\/a> 65(3), 1197-1231, 2024.<\/li>\n\n\n\n<li><strong>Jahn (2024)<\/strong><br>Jahn, M.: Artificial Neural Networks and Time Series of Counts: A Class of Nonlinear INGARCH Models.<br><a href=\"https:\/\/www.degruyterbrill.com\/journal\/key\/snde\/28\/5\/html\" rel='nofollow'>Studies in Nonlinear Dynamics &amp; Econometrics<\/a> 28(5), 751-765, 2024.<\/li>\n\n\n\n<li><strong>Nik (2024)<\/strong><br>Nik, S.: Marginal Analysis of Count Time Series in the Presence of Missing Observations.<br><a href=\"https:\/\/link.springer.com\/journal\/11749\/volumes-and-issues\/33-4\" rel='nofollow'>TEST<\/a> 33(4), 1105-1128, 2024.<\/li>\n\n\n\n<li><strong>Wei\u00df (2024d)<\/strong><br>Wei\u00df, C.H.: Ordinal compositional data and time series.<br><a href=\"https:\/\/journals.sagepub.com\/toc\/smja\/24\/6\" rel='nofollow'>Statistical Modelling<\/a> 24(6), 561-580, 2024.<\/li>\n\n\n\n<li><strong>Nik &amp; Wei\u00df (2024)<\/strong><br>Nik, S., Wei\u00df, C.H.: Generalized Moment Estimators based on Stein Identities.<br><a href=\"https:\/\/link.springer.com\/journal\/44199\/volumes-and-issues\/23-3\" rel='nofollow'>Journal of Statistical Theory and Applications<\/a> 23(3), 240-274, 2024.<\/li>\n\n\n\n<li><strong>Wei\u00df (2024c)<\/strong><br>Wei\u00df, C.H.: Control Charts for Poisson Counts based on the Stein-Chen Identity.<br><a href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-69111-9_9\" rel='nofollow'>Advanced Statistical Methods in Statistical Process Monitoring, Finance, and Environmental Science<\/a>, Springer, pp. 195&#8211;209, 2024 (<a href=\"https:\/\/arxiv.org\/abs\/2305.19006\" rel='nofollow'>arXiv preprint<\/a>).<\/li>\n\n\n\n<li><strong>Murat et al. (2024)<\/strong><br>Murat, U., Testik, M.C., Wei\u00df, C.H.: An Integrated Approach for Designing a Phase I c-Control Chart Based on the Phase II Performance of Poisson Exponentially Weighted Moving Average Control Chart.<br><a href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-69111-9_8\" rel='nofollow'>Advanced Statistical Methods in Statistical Process Monitoring, Finance, and Environmental Science<\/a>, Springer, pp. 173&#8211;194, 2024.<\/li>\n\n\n\n<li><strong>Wei\u00df (2024b)<\/strong><br>Wei\u00df, C.H.: Omnibus Control Charts for Poisson Counts.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/computers-and-industrial-engineering\/vol\/198\/suppl\/C\" rel='nofollow'>Computers &amp; Industrial Engineering<\/a> 198, 110615, 2024.<\/li>\n\n\n\n<li><strong>Aleksandrov et al. (2024)<\/strong><br>Aleksandrov, B., Wei\u00df, C.H., Nik, S., Faymonville, M., Jentsch, C.: Modelling and Diagnostic Tests for Poisson and Negative-binomial Count Time Series.<br><a href=\"https:\/\/link.springer.com\/journal\/184\/volumes-and-issues\/87-7\" rel='nofollow'>Metrika<\/a> 87(7), 843\u2013887, 2024.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Schnurr (2024)<\/strong><br>Wei\u00df, C.H., Schnurr, A.: Generalized ordinal patterns in discrete-valued time series: nonparametric testing for serial dependence.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/gnst20\/36\/3\" rel='nofollow'>Journal of Nonparametric Statistics<\/a> 36(3), 573-599, 2024.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Jahn (2024)<\/strong><br>Wei\u00df, C.H., Jahn, M.: Soft-clipping INGARCH models for time series of bounded counts.<br><a href=\"https:\/\/journals.sagepub.com\/toc\/smja\/24\/4\" rel='nofollow'>Statistical Modelling<\/a> 24(4), pp. 295-319, 2024.<\/li>\n\n\n\n<li><strong>Wei\u00df (2024a)<\/strong><br>Wei\u00df, C.H.: On Higher-Order Moments of INGARCH Processes.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/statistics-and-probability-letters\/vol\/214\/suppl\/C\" rel='nofollow'>Statistics and Probability Letters<\/a> 214, 110198, 2024.<\/li>\n\n\n\n<li><strong>Jahn &amp; Wei\u00df (2024)<\/strong><br>Jahn, M., Wei\u00df, C.H.: Nonlinear GARCH-type models for ordinal time series.<br><a href=\"https:\/\/link.springer.com\/journal\/477\/volumes-and-issues\/38-2\" rel='nofollow'>Stochastic Environmental Research and Risk Assessment<\/a> 38(2), 637-649, 2024.<\/li>\n\n\n\n<li><strong>Jahn (2024)<\/strong><br>Jahn, M.: A flexible likelihood-based neural network extension of the classic spatio-temporal model.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/spatial-statistics\/vol\/59\/suppl\/C\" rel='nofollow'>Spatial Statistics<\/a> 59, 100801, 2024.<\/li>\n\n\n\n<li><strong>Wang &amp; Wei\u00df (2024)<\/strong><br>Wang, H., Wei\u00df, C.H.: The Circumstance-driven Bivariate Integer-valued Autoregressive Model.<br><a href=\"https:\/\/www.mdpi.com\/1099-4300\/26\/2\" rel='nofollow'>Entropy<\/a> 26(2), 168, 2024.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Kim (2024)<\/strong><br>Wei\u00df, C.H., Kim, H.-Y.: Using Spatial Ordinal Patterns for Non-parametric Testing of Spatial Dependence.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/spatial-statistics\/vol\/59\/suppl\/C\" rel='nofollow'>Spatial Statistics<\/a> 59, 100800, 2024.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Zhu (2024)<\/strong><br>Wei\u00df, C.H., Zhu, F.: Conditional-mean Multiplicative Operator Models for Count Time Series.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/computational-statistics-and-data-analysis\/vol\/191\/suppl\/C\" rel='nofollow'>Computational Statistics and Data Analysis<\/a> 191, 107885, 2024.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2023<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Martins et al. (2023)<\/strong><br>Martins, A., Scotto, M.G., Wei\u00df, C.H., Gouveia, S.: Space-time integer-valued ARMA modelling for time series of counts.<br><a href=\"https:\/\/projecteuclid.org\/journals\/electronic-journal-of-statistics\/volume-17\/issue-2\" rel='nofollow'>Electronic Journal of Statistics<\/a> 17(2), 3472-3511, 2023.<\/li>\n\n\n\n<li><strong>Wei\u00df (2023)<\/strong><br>Wei\u00df, C.H.: Discrete-Valued Time Series.<br>Editorial, <a href=\"https:\/\/www.mdpi.com\/journal\/entropy\/special_issues\/Discrete_Valued_Time_Series\" rel='nofollow'>Entropy<\/a> 25(12), 1576, 2023.<\/li>\n\n\n\n<li><strong>L\u00f3pez-Oriona et al. (2023)<\/strong><br>L\u00f3pez-Oriona, \u00c1., Wei\u00df, C.H., Vilar, J.A.: Two novel distances for ordinal time series and their application to fuzzy clustering.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/fuzzy-sets-and-systems\/vol\/468\/suppl\/C\" rel='nofollow'>Fuzzy Sets and Systems<\/a> 468, 108590, 2023.<\/li>\n\n\n\n<li><strong>Ottenstreuer et al. (2023)<\/strong><br>Ottenstreuer, S., Wei\u00df, C.H., Testik, M.C.: A Review and Comparison of Control Charts for Ordinal Samples.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/ujqt20\/55\/4\" rel='nofollow'>Journal of Quality Technology<\/a> 55(4), pp. 422-441, 2023.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Testik (2023)<\/strong><br>Wei\u00df, C.H., Testik, M.C.: Non-parametric Control Charts for Monitoring Serial Dependence based on Ordinal Patterns.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/utch20\/65\/3\" rel='nofollow'>Technometrics<\/a> 65(3), pp. 340-350, 2023.<\/li>\n\n\n\n<li><strong>Faymonville et al. (2023)<\/strong><br>Faymonville, M., Jentsch, C., Wei\u00df, C.H., Aleksandrov, B.: Semiparametric estimation of INAR models using roughness penalization.<br><a href=\"https:\/\/link.springer.com\/journal\/10260\/volumes-and-issues\/32-2\" rel='nofollow'>Statistical Methods and Applications<\/a> 32(2), pp. 365-400, 2023.<\/li>\n\n\n\n<li><strong>Jahn et al. (2023)<\/strong><br>Jahn, M., Wei\u00df, C.H., Kim, H.-Y.: Approximately Linear INGARCH Models for Spatio-Temporal Counts.<br><a href=\"https:\/\/academic.oup.com\/jrsssc\/issue\/72\/2\" rel='nofollow'>Journal of the Royal Statistical Society (Series C)<\/a> 72(2), pp. 476-497, 2023.<\/li>\n\n\n\n<li><strong>Wang &amp; Wei\u00df (2023)<\/strong><br>Wang, S., Wei\u00df, C.H.: New Characterizations of the (Discrete) Lindley Distribution and their Applications.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/mathematics-and-computers-in-simulation\/vol\/212\/suppl\/C\" rel='nofollow'>Mathematics and Computers in Simulation<\/a> 212, pp. 310-322, 2023.<\/li>\n\n\n\n<li><strong>Homburg et al. (2023)<\/strong><br>Homburg, A., Wei\u00df, C.H., Alwan, L.C., Frahm, G., G\u00f6b, R.: PMF-Forecasting for Count Processes: A Comprehensive Performance Analysis.<br><a href=\"https:\/\/link.springer.com\/book\/9783031141966\" rel='nofollow'>Theory and Applications of Time Series Analysis and Forecasting: Selected Contributions from ITISE 2021<\/a>, Contributions to Statistics, Springer, pp. 79-90, 2023.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2023b)<\/strong><br>Wei\u00df, C.H., Puig, P., Aleksandrov, B.: Optimal Stein-type Goodness-of-Fit Tests for Count Data.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/15214036\/2023\/65\/2\" rel='nofollow'>Biometrical Journal<\/a> 65(2), 2200073, 2023.<\/li>\n\n\n\n<li><strong>Yu et al. (2023)<\/strong><br>Yu, K., Wang, H., Wei\u00df, C.H.: An Empirical-Likelihood-based Structural-Change Test for INAR Processes.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/gscs20\/93\/3\" rel='nofollow'>Journal of Statistical Computation and Simulation<\/a> 93(3), pp. 442-458, 2023.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2023a)<\/strong><br>Wei\u00df, C.H., Aleksandrov, B., Faymonville, M., Jentsch, C.: Partial Autocorrelation Diagnostics for Count Time Series.<br><a href=\"https:\/\/www.mdpi.com\/1099-4300\/25\/1\" rel='nofollow'>Entropy<\/a> 25(1), 105, <a href=\"https:\/\/www.mdpi.com\/journal\/entropy\/special_issues\/Discrete_Valued_Time_Series\" rel='nofollow'>Special Issue &#8222;Discrete-Valued Time Series&#8220;<\/a>, 2023.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2022<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Wei\u00df &amp; Testik (2022)<\/strong><br>Wei\u00df, C.H., Testik, M.C.: Monitoring Count Time Series: Robustness to Nonlinearity When Linear Models are Utilized.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/10991638\/2022\/38\/8\" rel='nofollow'>Quality and Reliability Engineering International<\/a> 38(8), pp. 4356-4371, 2022.<\/li>\n\n\n\n<li><strong>Aleksandrov et al. (2022b)<\/strong><br>Aleksandrov, B., Wei\u00df, C.H., Jentsch, C., Faymonville, M.: Novel Goodness-of-Fit Tests for Binomial Count Time Series.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/gsta20\/56\/5\" rel='nofollow'>Statistics<\/a> 56(5), pp. 957-990, 2022.<\/li>\n\n\n\n<li><strong>Wei\u00df (2022b)<\/strong><br>Wei\u00df, C.H.: Non-parametric Tests for Serial Dependence in Time Series based on Asymptotic Implementations of Ordinal-Pattern Statistics.<br><a href=\"https:\/\/aip.scitation.org\/toc\/cha\/32\/9\" rel='nofollow'>Chaos: An Interdisciplinary Journal of Nonlinear Science<\/a> 32(9), 093107, 2022.<br>(Focus Issue <a href=\"https:\/\/aip.scitation.org\/toc\/cha\/collection\/10.1063\/cha.2023.ORM2023.issue-1\" rel='nofollow'>&#8222;Ordinal Methods: Concepts, Applications, New Developments and Challenges&#8220;<\/a><\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2022c)<\/strong><br>Wei\u00df, C.H., Homburg, A., Alwan, L.C., Frahm, G., G\u00f6b, R.: Efficient Accounting for Estimation Uncertainty in Coherent Forecasting of Count Processes.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/cjas20\/49\/8\" rel='nofollow'>Journal of Applied Statistics<\/a> 49(8), pp. 1957-1978, 2022.<\/li>\n\n\n\n<li><strong>Ottenstreuer (2022)<\/strong><br>Ottenstreuer, S.: The Shiryaev-Roberts Control Chart for Markovian Count Time Series.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/10991638\/2022\/38\/3\" rel='nofollow'>Quality and Reliability Engineering International<\/a> 38(3), pp. 1207-1225, 2022.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2022b)<\/strong><br>Wei\u00df, C.H., Zhu, F., Hoshiyar, A.: Softplus INGARCH Models.<br><a href=\"http:\/\/www3.stat.sinica.edu.tw\/statistica\/j32n2\/32-2.html\" rel='nofollow'>Statistica Sinica<\/a> 32(2), pp. 1099-1120, 2022.<\/li>\n\n\n\n<li><strong>Nik &amp; Wei\u00df (2022)<\/strong><br>Nik, S., Wei\u00df, C.H.: Smooth-Transition Autoregressive Models for Time Series of Bounded Counts.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/lstm20\/37\/4\" rel='nofollow'>Stochastic Models<\/a> 37(4), pp. 568-588, 2022.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Aleksandrov (2022)<\/strong><br>Wei\u00df, C.H., Aleksandrov, B.: Computing (Bivariate) Poisson Moments using Stein\u2013Chen Identities.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/utas20\/76\/1\" rel='nofollow'>The American Statistician<\/a> 76(1), pp. 10-15, 2022.<\/li>\n\n\n\n<li><strong>Wei\u00df (2022a)<\/strong><br>Wei\u00df, C.H.: Measuring Dispersion and Serial Dependence in Ordinal Time Series based on the Cumulative Paired \u03d5-Entropy.<br><a href=\"https:\/\/www.mdpi.com\/1099-4300\/24\/1\" rel='nofollow'>Entropy<\/a> 24(1), 42, 2022.<\/li>\n\n\n\n<li><strong>Aleksandrov et al. (2022a)<\/strong><br>Aleksandrov, B., Wei\u00df, C.H., Jentsch, C.: Goodness-of-Fit Tests for Poisson Count Time Series based on the Stein-Chen Identity.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/14679574\/2022\/76\/1\" rel='nofollow'>Statistica Neerlandica<\/a> 76(1), pp. 35-64, 2022.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2022a)<\/strong><br>Wei\u00df, C.H., Ruiz Mar\u00edn, M., Keller, K., Matilla-Garc\u00eda, M.: Non-Parametric Analysis of Serial Dependence in Time Series using Ordinal Patterns.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/computational-statistics-and-data-analysis\/vol\/168\/suppl\/C\" rel='nofollow'>Computational Statistics and Data Analysis<\/a> 168, 107381, 2022.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2021<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Wei\u00df (2021e)<\/strong><br>Wei\u00df, C.H.: Time Series Modeling.<br>Editorial, <a href=\"https:\/\/www.mdpi.com\/journal\/entropy\/special_issues\/Time_Series_Model\" rel='nofollow'>Entropy<\/a> 23(9), 1163, 2021.<\/li>\n\n\n\n<li><strong>Wei\u00df (2021d)<\/strong><br>Wei\u00df, C.H.: On Approaches for Monitoring Categorical Event Series.<br>In K.P. Tran (ed.): <a href=\"https:\/\/link.springer.com\/book\/10.1007\/978-3-030-83819-5\" rel='nofollow'>Control Charts and Machine Learning for Anomaly Detection in Manufacturing<\/a>, Springer Series in Reliability Engineering, pp. 105-129, 2021.<\/li>\n\n\n\n<li><strong>Wei\u00df (2021c)<\/strong><br>Wei\u00df, C.H.: Analyzing Categorical Time Series in the Presence of Missing Observations.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/10970258\/2021\/40\/21\" rel='nofollow'>Statistics in Medicine<\/a> 40(21), pp. 4675-4690, 2021.<\/li>\n\n\n\n<li><strong>Homburg et al. (2021b)<\/strong><br>Homburg, A., Wei\u00df, C.H., Alwan, L.C., Frahm, G., G\u00f6b, R.: A Performance Analysis of Prediction Intervals for Count Time Series.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/1099131x\/2021\/40\/4\" rel='nofollow'>Journal of Forecasting<\/a> 40(4), pp. 603-625, 2021.<\/li>\n\n\n\n<li><strong>Morais et al. (2021)<\/strong><br>Morais, M.C., Knoth, S., Cruz, C.J., Wei\u00df, C.H.: ARL-unbiased CUSUM schemes to monitor binomial counts.<br>In Knoth &amp; Schmid (eds.): <a href=\"https:\/\/link.springer.com\/book\/10.1007\/978-3-030-67856-2\" rel='nofollow'>Frontiers in Statistical Quality Control 13<\/a>, pp. 77-98, 2021.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2021a)<\/strong><br>Wei\u00df, C.H., Testik, M.C., Homburg, A.: On the Design of Shewhart Control Charts for Count Time Series under Estimation Uncertainty.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/computers-and-industrial-engineering\/vol\/157\/suppl\/C\" rel='nofollow'>Computers &amp; Industrial Engineering<\/a> 157, 107331, 2021.<\/li>\n\n\n\n<li><strong>Homburg et al. (2021a)<\/strong><br>Homburg, A., Wei\u00df, C.H., Frahm, G., Alwan, L.C., G\u00f6b, R.: Analysis and Forecasting of Risk in Count Processes.<br><a href=\"https:\/\/www.mdpi.com\/1911-8074\/14\/4\" rel='nofollow'>Journal of Risk and Financial Management<\/a> 14(4), 182, 2021.<\/li>\n\n\n\n<li><strong>Ottenstreuer et al. (2021)<\/strong><br>Ottenstreuer, S., Wei\u00df, C.H., Knoth, S.: Control Charts for Monitoring a Poisson Hidden-Markov Process.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/10991638\/2021\/37\/2\" rel='nofollow'>Quality and Reliability Engineering International<\/a> 37(2), pp. 484-501, 2021.<\/li>\n\n\n\n<li><strong>Wei\u00df (2021b)<\/strong><br>Wei\u00df, C.H.: On Edgeworth Models for Count Time Series.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/statistics-and-probability-letters\/vol\/171\" rel='nofollow'>Statistics and Probability Letters<\/a> 171, 108994, 2021.<\/li>\n\n\n\n<li><strong>Wei\u00df (2021a)<\/strong><br>Wei\u00df, C.H.: Stationary Count Time Series Models.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/19390068\/2021\/13\/1\" rel='nofollow'>WIREs Computational Statistics<\/a> 13(1), e1502, 2021.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2020<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Homburg (2020)<\/strong><br>Homburg, A.: Criteria for Evaluating Approximations of Count Distributions.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/lssp20\/49\/12?nav=tocList\" rel='nofollow'>Communications in Statistics &#8211; Simulation and Computation<\/a> 49(12), pp. 3152-3170, 2020.<\/li>\n\n\n\n<li><strong>Nik &amp; Wei\u00df (2020)<\/strong><br>Nik, S., Wei\u00df, C.H.: CLAR(1) Point Forecasting under Estimation Uncertainty.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/14679574\/2020\/74\/4\" rel='nofollow'>Statistica Neerlandica<\/a> 74(4), pp. 489-516, 2020.<\/li>\n\n\n\n<li><strong>Kim et al. (2020)<\/strong><br>Kim, H.-Y., Wei\u00df, C.H., M\u00f6ller, T.A.: Models for Autoregressive Processes of Bounded Counts: How Different Are They?.<br><a href=\"https:\/\/link.springer.com\/journal\/180\/volumes-and-issues\/35-4\" rel='nofollow'>Computational Statistics<\/a> 35(4), pp. 1715-1736, 2020.<\/li>\n\n\n\n<li><strong>Wei\u00df (2020b)<\/strong><br>Wei\u00df, C.H.: Distance-based Analysis of Ordinal Data and Ordinal Time Series.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/uasa20\/115\/531\" rel='nofollow'>Journal of the American Statistical Association<\/a> 115(531), pp. 1189-1200, 2020.<\/li>\n\n\n\n<li><strong>Aleksandrov &amp; Wei\u00df (2020b)<\/strong><br>Aleksandrov, B., Wei\u00df, C.H.: Testing the Dispersion Structure of Count Time Series Using Pearson Residuals.<br><a href=\"https:\/\/link.springer.com\/journal\/10182\/volumes-and-issues\/104-3\" rel='nofollow'>AStA Advances in Statistical Analysis<\/a> 104(3), pp. 325-361, 2020.<\/li>\n\n\n\n<li><strong>M\u00f6ller &amp; Wei\u00df (2020)<\/strong><br>M\u00f6ller, T.A., Wei\u00df, C.H.: Generalized Discrete ARMA Models.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/15264025\/2020\/36\/4\" rel='nofollow'>Applied Stochastic Models in Business and Industry<\/a> 36(4), pp. 641-659, 2020.<\/li>\n\n\n\n<li><strong>Oh &amp; Wei\u00df (2020)<\/strong><br>Oh, J., Wei\u00df, C.H.: On the Individuals Chart with Supplementary Runs Rules under Serial Dependence.<br><a href=\"https:\/\/link.springer.com\/journal\/11009\/22\/3\" rel='nofollow'>Methodology and Computing in Applied Probability<\/a> 22(3), pp. 1257-1273, 2020.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2020)<\/strong><br>Wei\u00df, C.H., Scherer, L., Aleksandrov, B., Feld, M.H.-J.M.: Checking Model Adequacy for Count Time Series by Using Pearson Residuals.<br><a href=\"https:\/\/www.degruyter.com\/view\/journals\/jtse\/12\/1\/jtse.12.issue-1.xml\" rel='nofollow'>Journal of Time Series Econometrics<\/a> 12(1), 20180018, 2020.<\/li>\n\n\n\n<li><strong>Wei\u00df (2020a)<\/strong><br>Wei\u00df, C.H.: Regime-Switching Discrete ARMA Models for Categorical Time Series.<br><a href=\"https:\/\/www.mdpi.com\/1099-4300\/22\/4\" rel='nofollow'>Entropy<\/a> 22(4), 458, 2020.<\/li>\n\n\n\n<li><strong>Atalay et al. (2020)<\/strong><br>Atalay, M., Testik, M.C., Duran, S., Wei\u00df, C.H.: Guidelines for automating Phase I of control charts by considering effects on Phase-II performance of individuals control chart.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/lqen20\/32\/2?nav=tocList\" rel='nofollow'>Quality Engineering<\/a> 32(2), pp. 223-243, 2020.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Feld (2020)<\/strong><br>Wei\u00df, C.H., Feld, M.H.-J.M.: On the Performance of Information Criteria for Model Identification of Count Time Series.<br><a href=\"https:\/\/www.degruyter.com\/view\/journals\/snde\/24\/1\/snde.24.issue-1.xml\" rel='nofollow'>Studies in Nonlinear Dynamics &amp; Econometrics<\/a> 24(1), 20180012, 2020.<\/li>\n\n\n\n<li><strong>M\u00f6ller et al. (2020)<\/strong><br>M\u00f6ller, T.A., Wei\u00df, C.H., Kim, H.-Y.: Modeling Counts with State-Dependent Zero Inflation.<br><a href=\"https:\/\/journals.sagepub.com\/toc\/smja\/20\/2\" rel='nofollow'>Statistical Modelling<\/a> 20(2), pp. 127-147, 2020.<\/li>\n\n\n\n<li><strong>Aleksandrov &amp; Wei\u00df (2020a)<\/strong><br>Aleksandrov, B., Wei\u00df, C.H.: Parameter Estimation and Diagnostic Tests for INMA(1) Processes.<br><a href=\"https:\/\/link.springer.com\/journal\/11749\/29\/1\" rel='nofollow'>TEST<\/a> 29(1), pp. 196-232, 2020.<\/li>\n\n\n\n<li><strong>Puig &amp; Wei\u00df (2020)<\/strong><br>Puig, P., Wei\u00df, C.H.: Some goodness-of-fit tests for the Poisson distribution with applications in Biodosimetry.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/computational-statistics-and-data-analysis\/vol\/144\/suppl\/C\" rel='nofollow'>Computational Statistics and Data Analysis<\/a> 144, 106878, 2020.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2019<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Aleksandrov (2019)<\/strong><br>Aleksandrov, B.: A Negative-Binomial Index Considering Dispersion and Zero Probability.<br>In Steland et al. (eds.): <a href=\"https:\/\/link.springer.com\/book\/10.1007\/978-3-030-28665-1\" rel='nofollow'>Stochastic Models, Statistics and Their Applications<\/a>, Springer Proceedings in Mathematics &amp; Statistics, Vol. 294, Springer International Publishing, pp. 251-265, 2019.<\/li>\n\n\n\n<li><strong>Homburg (2019)<\/strong><br>Homburg, A.: Criteria to Validate Count Data Model Selection.<br>In Steland et al. (eds.): <a href=\"https:\/\/link.springer.com\/book\/10.1007\/978-3-030-28665-1\" rel='nofollow'>Stochastic Models, Statistics and Their Applications<\/a>, Springer Proceedings in Mathematics &amp; Statistics, Vol. 294, Springer International Publishing, pp. 429-436, 2019.<\/li>\n\n\n\n<li><strong>M\u00f6ller (2019)<\/strong><br>M\u00f6ller, T.M.: An Application of the Max-INAR(1) Model to Counts of Cinema Visitors.<br>In Steland et al. (eds.): <a href=\"https:\/\/link.springer.com\/book\/10.1007\/978-3-030-28665-1\" rel='nofollow'>Stochastic Models, Statistics and Their Applications<\/a>, Springer Proceedings in Mathematics &amp; Statistics, Vol. 294, Springer International Publishing, pp. 315-322, 2019.<\/li>\n\n\n\n<li><strong>Wei\u00df (2019c)<\/strong><br>Wei\u00df, C.H.: On the Sample Coefficient of Nominal Variation.<br>In Steland et al. (eds.): <a href=\"https:\/\/link.springer.com\/book\/10.1007\/978-3-030-28665-1\" rel='nofollow'>Stochastic Models, Statistics and Their Applications<\/a>, Springer Proceedings in Mathematics &amp; Statistics, Vol. 294, Springer International Publishing, pp. 239-250, 2019.<\/li>\n\n\n\n<li><strong>Wei\u00df (2019b)<\/strong><br>Wei\u00df, C.H.: On Some Measures of Ordinal Variation.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/cjas20\/46\/16\" rel='nofollow'>Journal of Applied Statistics<\/a> 46(16), pp. 2905-2926, 2019.<\/li>\n\n\n\n<li><strong>Adam et al. (2019)<\/strong><br>Adam, T., Langrock, R., Wei\u00df, C.H.: Penalized estimation of flexible hidden Markov models for time series of counts.<br><a href=\"https:\/\/link.springer.com\/journal\/40300\/77\/2\" rel='nofollow'>METRON<\/a> 77(2), pp. 87-104, 2019.<\/li>\n\n\n\n<li><strong>Homburg et al. (2019)<\/strong><br>Homburg, A., Wei\u00df, C.H., Alwan, L.C., Frahm, G., G\u00f6b, R.: Evaluating Approximate Point Forecasting of Count Processes.<br><a href=\"https:\/\/www.mdpi.com\/2225-1146\/7\/3\" rel='nofollow'>Econometrics<\/a> 7(3), 30, <a href=\"https:\/\/www.mdpi.com\/journal\/econometrics\/special_issues\/count_data\" rel='nofollow'>Special Issue &#8222;Discrete-Valued Time Series: Modelling, Estimation and Forecasting&#8220;<\/a>, 2019.<\/li>\n\n\n\n<li><strong>Jentsch &amp; Wei\u00df (2019)<\/strong><br>Jentsch, C., Wei\u00df, C.H.: Bootstrapping INAR models.<br><a href=\"https:\/\/projecteuclid.org\/euclid.bj\/1560326419\" rel='nofollow'>Bernoulli<\/a> 25(3), pp. 2359-2408, 2019.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2019b)<\/strong><br>Wei\u00df, C.H., Feld, M.H.-J.M., Mamode Khan, N., Sunecher, Y.: INARMA Modeling of Count Time Series.<br><a href=\"https:\/\/www.mdpi.com\/2571-905X\/2\/2\" rel='nofollow'>Stats<\/a> 2(2), pp. 284-320, 2019.<\/li>\n\n\n\n<li><strong>Ottenstreuer et al. (2019)<\/strong><br>Ottenstreuer, S., Wei\u00df, C.H., Knoth, S.: A Combined Shewhart-CUSUM Chart with Switching Limit.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/lqen20\/31\/2\" rel='nofollow'>Quality Engineering<\/a> 31(2), pp. 255-268, 2019.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2019a)<\/strong><br>Wei\u00df, C.H., Homburg, A., Puig, P.: Testing for Zero Inflation and Overdispersion in INAR(1) Models.<br><a href=\"https:\/\/link.springer.com\/journal\/362\/60\/3\/page\/1\" rel='nofollow'>Statistical Papers<\/a> 60(3), pp. 823-848, 2019.<\/li>\n\n\n\n<li><strong>Wei\u00df (2019a)<\/strong><br>Wei\u00df, C.H.: Measures of Dispersion and Serial Dependence in Categorical Time Series.<br><a href=\"https:\/\/www.mdpi.com\/2225-1146\/7\/2\" rel='nofollow'>Econometrics<\/a> 7(2), 17, <a href=\"https:\/\/www.mdpi.com\/journal\/econometrics\/special_issues\/count_data\" rel='nofollow'>Special Issue &#8222;Discrete-Valued Time Series: Modelling, Estimation and Forecasting&#8220;<\/a>, 2019.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Jentsch (2019)<\/strong><br>Wei\u00df, C.H., Jentsch, C.: Bootstrap-based Bias Corrections for INAR Count Time Series.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/gscs20\/89\/7\" rel='nofollow'>Journal of Statistical Computation and Simulation<\/a> 89(7), pp. 1248-1264, 2019.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Aleksandrov (2019)<\/strong><br>Wei\u00df, C.H., Aleksandrov, B.: Model diagnostics for Poisson INARMA processes using bivariate dispersion indexes.<br><a href=\"https:\/\/link.springer.com\/journal\/42519\/13\/2\" rel='nofollow'>Journal of Statistical Theory and Practice<\/a> 13(2), article 26, pp. 1-28, 2019.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Testik (2019)<\/strong><br>Wei\u00df, C.H., Testik, M.C.: Risk-Based Metrics for Performance Evaluation of Control Charts.<br><a href=\"https:\/\/onlinelibrary.wiley.com\/toc\/10991638\/2019\/35\/1\" rel='nofollow'>Quality and Reliability Engineering International<\/a> 35(1), pp. 280-291, 2019.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2018<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Morais et al. (2018)<\/strong><br>Morais, M.C., Knoth, S., Wei\u00df, C.H.: An ARL-unbiased thinning-based EWMA chart to monitor counts.<br><a href=\"https:\/\/www.tandfonline.com\/toc\/lsqa20\/37\/4\" rel='nofollow'>Sequential Analysis<\/a> 37(4), pp. 487-510, 2018.<\/li>\n\n\n\n<li><strong>Scotto et al. (2018)<\/strong><br>Scotto, M.G., Wei\u00df, C.H., M\u00f6ller, T.A., Gouveia, S.: The Max-INAR(1) model for count processes.<br><a href=\"https:\/\/link.springer.com\/journal\/11749\/27\/4\/page\/1\" rel='nofollow'>TEST<\/a> 27(4), pp. 850-870, 2018.<\/li>\n\n\n\n<li><strong>Kim et al. (2018)<\/strong><br>Kim, H.-Y., Wei\u00df, C.H., M\u00f6ller, T.A.: Testing for an excessive number of zeros in time series of bounded counts.<br><a href=\"https:\/\/link.springer.com\/journal\/10260\/27\/4\/page\/1\" rel='nofollow'>Statistical Methods &amp; Applications<\/a> 27(4), pp. 689-714, 2018.<\/li>\n\n\n\n<li><strong>Gouveia et al. (2018)<\/strong><br>Gouveia, S., M\u00f6ller, T.A., Wei\u00df, C.H., Scotto, M.G.: A full ARMA model for counts with bounded support and its application to rainy-days time series.<br><a href=\"https:\/\/link.springer.com\/journal\/477\/32\/9\/page\/1\" rel='nofollow'>Stochastic Environmental Research and Risk Assessment<\/a> 32(9), pp. 2495-2514, 2018.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2018b)<\/strong><br>Wei\u00df, C.H., Steuer, D., Jentsch, C., Testik, M.C.: Guaranteed Conditional ARL Performance in the Presence of Autocorrelation.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/computational-statistics-and-data-analysis\/vol\/128\/suppl\/C\" rel='nofollow'>Computational Statistics and Data Analysis<\/a> 128, pp. 367-379, 2018.<\/li>\n\n\n\n<li><strong>Wei\u00df (2018g)<\/strong><br>Wei\u00df, C.H.: Categorical Time Series Analysis.<br>In Balakrishnan et al. (eds.): <a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/9781118445112.stat08132\/full\" rel='nofollow'>Wiley StatsRef: Statistics Reference Online<\/a>, John Wiley &amp; Sons Ltd, 2018.<\/li>\n\n\n\n<li><strong>Wei\u00df (2018f)<\/strong><br>Wei\u00df, C.H.: Count Time Series Analysis.<br>In Balakrishnan et al. (eds.): <a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/9781118445112.stat08131\/full\" rel='nofollow'>Wiley StatsRef: Statistics Reference Online<\/a>, John Wiley &amp; Sons Ltd, 2018.<\/li>\n\n\n\n<li><strong>Wei\u00df (2018e)<\/strong><br>Wei\u00df, C.H.: Integer-valued Autoregressive Moving-Average (INARMA) Models.<br>In Balakrishnan et al. (eds.): <a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/9781118445112.stat08133\/full\" rel='nofollow'>Wiley StatsRef: Statistics Reference Online<\/a>, John Wiley &amp; Sons Ltd, 2018.<\/li>\n\n\n\n<li><strong>Wei\u00df (2018d)<\/strong><br>Wei\u00df, C.H.: INGARCH and Regression Models for Count Time Series.<br>In Balakrishnan et al. (eds.): <a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/9781118445112.stat08134\/full\" rel='nofollow'>Wiley StatsRef: Statistics Reference Online<\/a>, John Wiley &amp; Sons Ltd, 2018.<\/li>\n\n\n\n<li><strong>Wei\u00df (2018c)<\/strong><br>Wei\u00df, C.H.: Hidden-Markov Models for Count Time Series.<br>In Balakrishnan et al. (eds.): <a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/9781118445112.stat08135\/full\" rel='nofollow'>Wiley StatsRef: Statistics Reference Online<\/a>, John Wiley &amp; Sons Ltd, 2018.<\/li>\n\n\n\n<li><strong>Wei\u00df (2018b)<\/strong><br>Wei\u00df, C.H.: Goodness-of-Fit Testing of a Count Time Series&#8216; Marginal Distribution.<br><a href=\"https:\/\/link.springer.com\/journal\/184\/81\/6\/page\/1\" rel='nofollow'>Metrika<\/a> 81(6), pp. 619-651, 2018.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2018a)<\/strong><br>Wei\u00df, C.H., Scotto, M.G., M\u00f6ller, T.A., Gouveia, S.: The max-BARMA models for Counts with Bounded Support.<br><a href=\"https:\/\/www.sciencedirect.com\/journal\/statistics-and-probability-letters\/vol\/143\/suppl\/C\" rel='nofollow'>Statistics &amp; Probability Letters<\/a> 143, pp. 28-36, 2018.<\/li>\n\n\n\n<li><strong>Wei\u00df (2018a)<\/strong><br>Wei\u00df, C.H.: Control Charts for Time-Dependent Categorical Processes.<br>In Knoth &amp; Schmid (eds.): <a href=\"https:\/\/www.springer.com\/de\/book\/9783319752945\" rel='nofollow'>Frontiers in Statistical Quality Control 12<\/a>, pp. 211-231, 2018.<\/li>\n\n\n\n<li><strong>Testik et al. (2018b)<\/strong><br>Testik, M.C., Wei\u00df, C.H., Koca, Y., Testik, O.M.: Assessment of Shewhart Control Chart Limits in Phase I Implementations under Various Shift and Contamination Scenarios.<br>In Knoth &amp; Schmid (eds.): <a href=\"https:\/\/www.springer.com\/de\/book\/9783319752945\" rel='nofollow'>Frontiers in Statistical Quality Control 12<\/a>, pp. 21-43, 2018.<\/li>\n\n\n\n<li><strong>M\u00f6ller et al. (2018)<\/strong><br>M\u00f6ller, T.A., Wei\u00df, C.H., Kim, H.-Y., Sirchenko, A.: Modeling Zero Inflation in Count Data Time Series with Bounded Support.<br><a href=\"https:\/\/link.springer.com\/journal\/11009\/20\/2\/page\/1\" rel='nofollow'>Methodology and Computing in Applied Probability<\/a> 20(2), pp. 589-609, 2018.<\/li>\n\n\n\n<li><strong>Testik et al. (2018a)<\/strong><br>Testik, M.C., Wei\u00df, C.H., Koca, Y., Testik, O.M.: Effectiveness of Phase-I Applications for Identifying Randomly Scattered Out-of-Control Observations and Estimating Control Chart Parameters.<br><a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/qre.v34.1\/issuetoc\" rel='nofollow'>Quality and Reliability Engineering International<\/a> 34(1), pp. 78-92, 2018.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2017<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Rakitzis et al. (2017b)<\/strong><br>Rakitzis, A.C., Wei\u00df, C.H., Castagliola, P.: Control Charts for Monitoring Correlated Counts with a Finite Range.<br><a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/asmb.v33.6\/issuetoc\" rel='nofollow'>Applied Stochastic Models in Business and Industry<\/a> 33(6), pp. 733-749, 2017.<\/li>\n\n\n\n<li><strong>Wei\u00df (2017b)<\/strong><br>Wei\u00df, C.H.: Association Rule Mining.<br>In Balakrishnan et al. (eds.): <a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/9781118445112.stat08016\/full\" rel='nofollow'>Wiley StatsRef: Statistics Reference Online<\/a>, John Wiley &amp; Sons Ltd, 2017.<\/li>\n\n\n\n<li><strong>Bourguignon &amp; Wei\u00df (2017)<\/strong><br>Bourguignon, M., Wei\u00df, C.H.: An INAR(1) process for modeling count time series with equidispersion, underdispersion and overdispersion.<br><a href=\"https:\/\/link.springer.com\/journal\/11749\/26\/4\/page\/1\" rel='nofollow'>TEST<\/a> 26(4), pp. 847-868, 2017.<\/li>\n\n\n\n<li><strong>Wei\u00df (2017a)<\/strong><br>Wei\u00df, C.H.: On Eigenvalues of the Transition Matrix of some Count-Data Markov Chains.<br><a href=\"https:\/\/link.springer.com\/journal\/11009\/19\/3\/page\/1\" rel='nofollow'>Methodology and Computing in Applied Probability<\/a> 19(3), pp. 997-1007, 2017.<\/li>\n\n\n\n<li><strong>Wei\u00df et al. (2017)<\/strong><br>Wei\u00df, C.H., Gon\u00e7alves, E., Mendes Lopes, N.: Testing the Compounding Structure of the CP-INARCH Model.<br><a href=\"https:\/\/link.springer.com\/journal\/184\/80\/5\/page\/1\" rel='nofollow'>Metrika<\/a> 80(5), pp. 571-603, 2017.<\/li>\n\n\n\n<li><strong>Rakitzis et al. (2017a)<\/strong><br>Rakitzis, A.C., Wei\u00df, C.H., Castagliola, P.: Control Charts for Monitoring Correlated Poisson Counts with an Excessive Number of Zeros.<br><a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/qre.v33.2\/issuetoc\" rel='nofollow'>Quality and Reliability Engineering International<\/a> 33(2), pp. 413-430, 2017.<\/li>\n\n\n\n<li><strong>Gouveia et al. (2017)<\/strong><br>Gouveia, S., Scotto, M.G., Wei\u00df, C.H., Ferreira, P.J.S.G.: Binary autoregressive geometric modelling in a DNA context.<br><a href=\"https:\/\/academic.oup.com\/jrsssc\/issue\/66\/2\" rel='nofollow'>Journal of the Royal Statistical Society (Series C)<\/a> 66(2), pp. 253-271, 2017.<\/li>\n\n\n\n<li><strong>Alwan &amp; Wei\u00df (2017)<\/strong><br>Alwan, L.C., Wei\u00df, C.H.: INAR Implementation of Newsvendor Model for Serially Dependent Demand Counts.<br><a href=\"http:\/\/www.tandfonline.com\/toc\/tprs20\/55\/4\" rel='nofollow'>International Journal of Production Research<\/a> 55(4), pp. 1085-1099, 2017.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2016<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Risti\u0107 et al. (2016)<\/strong><br>Risti\u0107, M.M., Wei\u00df, C.H., Janji\u0107, A.D.: A binomial integer-valued ARCH model.<br><a href=\"https:\/\/www.degruyter.com\/view\/journals\/ijb\/12\/2\/ijb.12.issue-2.xml\" rel='nofollow'>International Journal of Biostatistics<\/a> 12(2), 20150051, 2016.<\/li>\n\n\n\n<li><strong>M\u00f6ller et al. (2016)<\/strong><br>M\u00f6ller, T.A., Silva, M.E., Wei\u00df, C.H., Scotto, M.G., Pereira, I.: Self-Exciting Threshold Binomial Autoregressive Processes.<br><a href=\"http:\/\/link.springer.com\/journal\/10182\/100\/4\/page\/1\" rel='nofollow'>Advances in Statistical Analysis<\/a> 100(4), pp. 369-400, 2016.<\/li>\n\n\n\n<li><strong>Schweer &amp; Wei\u00df (2016)<\/strong><br>Schweer, S., Wei\u00df, C.H.: Testing for Poisson Arrivals in INAR(1) Processes.<br><a href=\"http:\/\/link.springer.com\/journal\/11749\/25\/3\/page\/1\" rel='nofollow'>TEST<\/a> 25(3), pp. 503-524, 2016.<\/li>\n\n\n\n<li><strong>Dasdemir et al. (2016)<\/strong><br>Dasdemir, E., Wei\u00df, C.H., Testik, M.C., Knoth, S.: Evaluation of Phase I analysis scenarios on Phase II performance of control charts for autocorrelated observations.<br><a href=\"http:\/\/www.tandfonline.com\/toc\/lqen20\/28\/3\" rel='nofollow'>Quality Engineering<\/a> 28(3), pp. 293-304, 2016.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Schweer (2016)<\/strong><br>Wei\u00df, C.H., Schweer, S.: Bias Corrections for Moment Estimators in Poisson INAR(1) and INARCH(1) Processes.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/01677152\/112\" rel='nofollow'>Statistics and Probability Letters<\/a> 112, pp. 124-130, 2016.<\/li>\n\n\n\n<li><strong>M\u00f6ller (2016)<\/strong><br>M\u00f6ller, T.A.: Self-Exciting Threshold Models for Time Series of Counts with a Finite Range.<br><a href=\"http:\/\/www.tandfonline.com\/toc\/lstm20\/32\/1\" rel='nofollow'>Stochastic Models<\/a> 32(1), pp. 77-98, 2016.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2015<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Scotto et al. (2015)<\/strong><br>Scotto, M.G., Wei\u00df, C.H., Gouveia, S.: Thinning-based models in the analysis of integer-valued time series: a review.<br><a href=\"http:\/\/smj.sagepub.com\/content\/15\/6.toc\" rel='nofollow'>Statistical Modelling<\/a> 15(6), pp. 590-618, 2015.<\/li>\n\n\n\n<li><strong>Freyn &amp; Wei\u00df (2015)<\/strong><br>Freyn, W., Wei\u00df, C.H.: Neue Ma\u00dfnahmen f\u00fcr eine verbesserte Schulung und Betreuung von \u00dcbungsleitern.<br>In Hoppenbrock et al. ( <abbr title=\"Herausgeber\">Hrsg.<\/abbr>), <a href=\"http:\/\/www.springer.com\/de\/book\/9783658102609\" rel='nofollow'>Lehren und Lernen von Mathematik in der Studieneingangsphase &#8211; Herausforderungen und L\u00f6sungsans\u00e4tze<\/a>, pp. 213-227, 2015.<\/li>\n\n\n\n<li><strong>Wei\u00df (2015c)<\/strong><br>Wei\u00df, C.H.: SPC Methods for Time-Dependent Processes of Counts &#8211; A Literature Review.<br><a href=\"http:\/\/cogentoa.tandfonline.com\/article-list\/oama20\/2\/1?startPage=&amp;ConceptID=oama-sta\" rel='nofollow'>Cogent Mathematics<\/a> 2(1): 1111116, 2015.<\/li>\n\n\n\n<li><strong>Wei\u00df (2015b)<\/strong><br>Wei\u00df, C.H.: A Poisson INAR(1) Model with Serially Dependent Innovations.<br><a href=\"http:\/\/link.springer.com\/journal\/184\/78\/7\/page\/1\" rel='nofollow'>Metrika<\/a> 78(7), pp. 829-851, 2015.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Schweer (2015)<\/strong><br>Wei\u00df, C.H., Schweer, S.: Detecting Overdispersion in INARCH(1) Processes.<br><a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/stan.v69.3\/issuetoc\" rel='nofollow'>Statistica Neerlandica<\/a> 69(3), pp. 281-297, 2015.<\/li>\n\n\n\n<li><strong>Wei\u00df (2015a)<\/strong><br>Wei\u00df, C.H.: Sampling in Data Mining.<br>In Balakrishnan et al. (Eds.): <a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/9781118445112.stat04222.pub2\" rel='nofollow'>Wiley StatsRef: Statistics Reference Online<\/a>, John Wiley &amp; Sons Ltd, 2015.<\/li>\n\n\n\n<li><strong>Kim &amp; Wei\u00df (2015)<\/strong><br>Kim, H.-Y., Wei\u00df, C.H.: Goodness-of-Fit Tests for Binomial AR(1) Processes.<br><a href=\"http:\/\/www.tandfonline.com\/toc\/gsta20\/49\/2\" rel='nofollow'>Statistics: A Journal of Theoretical and Applied Statistics<\/a> 49(2), pp. 291-315, 2015.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Testik (2015b)<\/strong><br>Wei\u00df, C.H., Testik, M.C.: On the Phase I Analysis for Monitoring Time-Dependent Count Processes.<br><a href=\"http:\/\/www.tandfonline.com\/toc\/uiie20\/47\/3\" rel='nofollow'>IIE Transactions<\/a> 47(3), pp. 294-306, 2015.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Testik (2015a)<\/strong><br>Wei\u00df, C.H., Testik, M.C.: Residuals-based CUSUM Charts for Poisson INAR(1) Processes.<br><a href=\"http:\/\/asq.org\/pub\/jqt\/past\/vol47-issue1\/index.html\" rel='nofollow'>Journal of Quality Technology<\/a> 47(1), pp. 30-42, 2015.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Puig (2015)<\/strong><br>Wei\u00df, C.H., Puig, P.: The Marginal Distribution of Compound Poisson INAR(1) Processes.<br>Steland et al. (eds.): <a href=\"https:\/\/link.springer.com\/book\/10.1007\/978-3-319-13881-7\" rel='nofollow'>Stochastic Models, Statistics and Their Applications<\/a>, Springer Proceedings in Mathematics &amp; Statistics 122, Springer-Verlag, pp. 351-359, 2015.<\/li>\n\n\n\n<li><strong>M\u00f6ller &amp; Wei\u00df (2015)<\/strong><br>M\u00f6ller, T.A., Wei\u00df, C.H.: Threshold models for integer-valued time series with infinite and finite range.<br>Steland et al. (eds.): <a href=\"https:\/\/link.springer.com\/book\/10.1007\/978-3-319-13881-7\" rel='nofollow'>Stochastic Models, Statistics and Their Applications<\/a>, Springer Proceedings in Mathematics &amp; Statistics 122, Springer-Verlag, pp. 327-334, 2015.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2014<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Wei\u00df &amp; Kim (2014)<\/strong><br>Wei\u00df, C.H., Kim, H.-Y.: Diagnosing and Modelling Extra-Binomial Variation for Time-Dependent Counts.<br><a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/asm.v30.5\/issuetoc\" rel='nofollow'>Applied Stochastic Models in Business and Industry<\/a> 30(5), pp. 588-608, 2014.<\/li>\n\n\n\n<li><strong>Schweer &amp; Wei\u00df (2014)<\/strong><br>Schweer, S., Wei\u00df, C.H.: Compound Poisson INAR(1) Processes: Stochastic Properties and Testing for Overdispersion.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/01679473\/77\" rel='nofollow'>Computational Statistics and Data Analysis<\/a> 77, pp. 267-284, 2014.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Pollett (2014)<\/strong><br>Wei\u00df, C.H., Pollett, P.K.: Binomial Autoregressive Processes with Density Dependent Thinning.<br><a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/jtsa.v35.2\/issuetoc\" rel='nofollow'>Journal of Time Series Analysis<\/a> 35(2), pp. 115-132, 2014.<\/li>\n\n\n\n<li><strong>Scotto et al. (2014)<\/strong><br>Scotto, M.G., Wei\u00df, C.H., Silva, M.E., Pereira, I.: Bivariate Binomial Autoregressive Models.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/0047259X\/125\" rel='nofollow'>Journal of Multivariate Analysis<\/a> 125, pp. 233-251, 2014.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2013<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Freyn &amp; Wei\u00df (2013)<\/strong><br>Freyn, W., Wei\u00df, C.H.: Schulung und Betreuung von \u00dcbungsleitern in der mathematischen Grundausbildung.<br>In Hoppenbrock et al. ( <abbr title=\"Herausgeber\">Hrsg.<\/abbr>), Mathematik im \u00dcbergang Schule\/Hochschule und im ersten Studienjahr &#8212; <a href=\"http:\/\/nbn-resolving.de\/urn:nbn:de:hebis:34-2013081343293\" rel='nofollow'>Extended Abstracts zur 2. khdm-Arbeitstagung<\/a>, khdm-Report 13-01, Kassel, pp. 55-56, 2013.<\/li>\n\n\n\n<li><strong>Wei\u00df (2013c)<\/strong><br>Wei\u00df, C.H.: Integer-valued Autoregressive Models for Counts Showing Underdispersion.<br><a href=\"http:\/\/www.tandfonline.com\/toc\/cjas20\/40\/9\" rel='nofollow'>Journal of Applied Statistics<\/a> 40(9), pp. 1931-1948, 2013.<\/li>\n\n\n\n<li><strong>Wei\u00df (2013b)<\/strong><br>Wei\u00df, C.H.: Serial Dependence of NDARMA Processes.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/01679473\/68\" rel='nofollow'>Computational Statistics &amp; Data Analysis<\/a> 68, pp. 213-238, 2013.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Kim (2013b)<\/strong><br>Wei\u00df, C.H., Kim, H.-Y.: Parameter Estimation for Binomial AR(1) Models with Applications in Finance and Industry.<br><a href=\"http:\/\/link.springer.com\/journal\/362\/54\/3\/page\/1\" rel='nofollow'>Statistical Papers<\/a> 54(3), pp. 563-590, 2013.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Kim (2013a)<\/strong><br>Wei\u00df, C.H., Kim, H.-Y.: Binomial AR(1) Processes: Moments, Cumulants, and Estimation.<br><a href=\"http:\/\/www.tandfonline.com\/toc\/gsta20\/47\/3\" rel='nofollow'>Statistics: A Journal of Theoretical and Applied Statistics<\/a> 47(3), pp. 494-510, 2013.<\/li>\n\n\n\n<li><strong>Wei\u00df (2013a)<\/strong><br>Wei\u00df, C.H.: Monitoring k-th Order Runs in Binary Processes.<br><a href=\"http:\/\/link.springer.com\/journal\/180\/28\/2\/page\/1\" rel='nofollow'>Computational Statistics<\/a> 28(2), pp. 541-563, 2013.<\/li>\n\n\n\n<li><strong>Yontay et al. (2013)<\/strong><br>Yontay, P., Wei\u00df, C.H., Testik, M.C., Bayindir, Z.P.: A Two-Sided CUSUM Chart for First-Order Integer-Valued Autoregressive Processes of Poisson Counts.<br><a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/qre.v29.1\/issuetoc\" rel='nofollow'>Quality and Reliability Engineering International<\/a> 29(1), pp. 33-42, 2013.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Peltola (2013)<\/strong><br>Wei\u00df, C.H., Peltola, M.: Sequential Pattern Analysis: A Statistical Investigation of Sequence Length and Support.<br><a href=\"http:\/\/www.tandfonline.com\/toc\/lssp20\/42\/5\" rel='nofollow'>Communications in Statistics &#8211; Simulation and Computation<\/a> 42(5), pp. 1044-1062, 2013.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2012<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Wei\u00df &amp; Pollett (2012)<\/strong><br>Wei\u00df, C.H., Pollett, P.K.: Chain Binomial Models and Binomial Autoregressive Processes.<br><a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/biom.2012.68.issue-3\/issuetoc\" rel='nofollow'>Biometrics<\/a> 68(3), pp. 815-824, 2012.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Testik (2012)<\/strong><br>Wei\u00df, C.H., Testik, M.C.: Detection of Abrupt Changes in Count Data Time Series: Cumulative Sum Derivations for INARCH(1) Models.<br><a href=\"http:\/\/asq.org\/pub\/jqt\/past\/vol44-issue3\/index.html\" rel='nofollow'>Journal of Quality Technology<\/a> 44(3), pp. 249-264, 2012.<\/li>\n\n\n\n<li><strong>Wei\u00df (2012c)<\/strong><br>Wei\u00df, C.H.: Process Capability Analysis for Serially Dependent Processes of Poisson Counts.<br><a href=\"http:\/\/www.tandfonline.com\/toc\/gscs20\/82\/3\" rel='nofollow'>Journal of Statistical Computation and Simulation<\/a> 82(3), pp. 383-404, 2012.<\/li>\n\n\n\n<li><strong>Wei\u00df (2012b)<\/strong><br>Wei\u00df, C.H.: Fully Observed INAR(1) Processes.<br><a href=\"http:\/\/www.tandfonline.com\/toc\/cjas20\/39\/3\" rel='nofollow'>Journal of Applied Statistics<\/a> 39(3), pp. 581-598, 2012.<\/li>\n\n\n\n<li><strong>Wei\u00df (2012a)<\/strong><br>Wei\u00df, C.H.: Continuously Monitoring Categorical Processes.<br><a href=\"http:\/\/tandfonline.com\/toc\/ttqm20\/9\/2\" rel='nofollow'>Quality Technology and Quantitative Management<\/a> 9(2), pp. 171-188, 2012.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2011<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Wei\u00df (2011f)<\/strong><br>Wei\u00df, C.H.: Simultaneous Confidence Regions for the Parameters of a Poisson INAR(1) Model.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/15723127\/8\/6\" rel='nofollow'>Statistical Methodology<\/a> 8(6), pp. 517-527, 2011.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Testik (2011)<\/strong><br>Wei\u00df, C.H., Testik, M.C.: The Poisson INAR(1) CUSUM Chart under Overdispersion and Estimation Error.<br><a href=\"http:\/\/www.tandfonline.com\/toc\/uiie20\/43\/11\" rel='nofollow'>IIE Transactions<\/a> 43(11), pp. 805-818, 2011.<\/li>\n\n\n\n<li><strong>Wei\u00df (2011e)<\/strong><br>Wei\u00df, C.H.: Generalized Choice Models for Categorical Time Series.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/03783758\/141\/8\" rel='nofollow'>Journal of Statistical Planning and Inference<\/a> 141(8), pp. 2849-2862, 2011.<\/li>\n\n\n\n<li><strong>Wei\u00df (2011d)<\/strong><br>Wei\u00df, C.H.: Empirical Measures of Signed Serial Dependence in Categorical Time Series.<br><a href=\"http:\/\/www.informaworld.com\/smpp\/title~db=all~content=g934844042\" rel='nofollow'>Journal of Statistical Computation and Simulation<\/a> 81(4), pp. 411-429, 2011.<\/li>\n\n\n\n<li><strong>Wei\u00df (2011c)<\/strong><br>Wei\u00df, C.H.: The Markov Chain Approach for Performance Evaluation of Control Charts &#8211; A Tutorial.<br>Chapter 11 in Samuel P. Werther (Ed.): <a href=\"https:\/\/www.novapublishers.com\/catalog\/product_info.php?products_id=17460\" rel='nofollow'>Process Control: Problems, Techniques and Applications<\/a>, <abbr title=\"International Standard Book Number\">ISBN<\/abbr> 978-1-61209-567-7, Nova Science Publishers, Inc., pp. 205-228, 2011.<\/li>\n\n\n\n<li><strong>Wei\u00df (2011b)<\/strong><br>Wei\u00df, C.H.: Rule Generation for Categorical Time Series with Markov Assumptions.<br><a href=\"http:\/\/link.springer.com\/journal\/11222\/21\/1\/page\/1\" rel='nofollow'>Statistics and Computing<\/a> 21(1), pp. 1-16, 2011.<\/li>\n\n\n\n<li><strong>Wei\u00df (2011a)<\/strong><br>Wei\u00df, C.H.: Detecting Mean Increases in Poisson INAR(1) Processes with EWMA Control Charts.<br><a href=\"http:\/\/www.informaworld.com\/smpp\/title~db=all~content=g930877320\" rel='nofollow'>Journal of Applied Statistics<\/a> 38(2), pp. 383-398, 2011.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2010<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Wei\u00df &amp; Atzm\u00fcller (2010)<\/strong><br>Wei\u00df, C.H., Atzm\u00fcller, M.: EWMA Control Charts for Monitoring Binary Processes with Applications to Medical Diagnosis Data.<br><a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/qre.v26.8\/issuetoc\" rel='nofollow'>Quality and Reliability Engineering International<\/a> 26(8), pp. 795-805, 2010.<\/li>\n\n\n\n<li><strong>Wei\u00df (2010c)<\/strong><br>Wei\u00df, C.H.: INARCH(1) Processes: Higher-Order Moments and Jumps.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/01677152\/80\/23-24\" rel='nofollow'>Statistics and Probability Letters<\/a> 80(23-24), pp. 1771-1780, 2010.<\/li>\n\n\n\n<li><strong>Ozsan et al. (2010)<\/strong><br>Ozsan, G., Testik, M.C., Wei\u00df, C.H.: Properties of the Exponential EWMA Chart with Parameter Estimatation.<br><a href=\"http:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/qre.v26:6\/issuetoc\" rel='nofollow'>Quality and Reliability Engineering International<\/a> 26(6), pp. 555-569, 2010.<\/li>\n\n\n\n<li><strong>Wei\u00df (2010b)<\/strong><br>Wei\u00df, C.H.: On New Perspectives for Statistical Computing in Business and Industry &#8211; A Solution with STATISTICA and R.<br><a href=\"https:\/\/www.degruyter.com\/view\/journals\/eqc\/25\/1\/eqc.25.issue-1.xml\" rel='nofollow'>Economic Quality Control<\/a> 25(1), pp. 43-64, 2010.<\/li>\n\n\n\n<li><strong>Wei\u00df (2010a)<\/strong><br>Wei\u00df, C.H.: The INARCH(1) Model for Overdispersed Time Series of Counts.<br><a href=\"http:\/\/www.informaworld.com\/smpp\/title~db=jour~content=g922059857\" rel='nofollow'>Communications in Statistics &#8211; Simulation and Computation<\/a> 39(6), pp. 1269-1291, 2010.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2009<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Wei\u00df (2009i)<\/strong><br>Wei\u00df, C.H.: Controlling Jumps in Correlated Processes of Poisson Counts.<br><a href=\"http:\/\/www3.interscience.wiley.com\/journal\/122652159\/issue\" rel='nofollow'>Applied Stochastic Models in Business and Industry<\/a> 25(5), pp. 551-564, 2009.<\/li>\n\n\n\n<li><strong>Wei\u00df (2009h)<\/strong><br>Wei\u00df, C.H.: Modelling Time Series of Counts with Overdispersion.<br><a href=\"http:\/\/link.springer.com\/journal\/10260\/18\/4\/page\/1\" rel='nofollow'>Statistical Methods and Applications<\/a> 18(4), pp. 507-519, 2009.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; Testik (2009)<\/strong><br>Wei\u00df, C.H., Testik, M.C.: CUSUM Monitoring of First-Order Integer-Valued Autoregressive Processes of Poisson Counts.<br><a href=\"http:\/\/www.asq.org\/pub\/jqt\/past\/vol41-issue4\/index.html\" rel='nofollow'>Journal of Quality Technology<\/a> 41(4), pp. 389-400, 2009.<\/li>\n\n\n\n<li><strong>Wei\u00df (2009g)<\/strong><br>Wei\u00df, C.H.: Jumps in Binomial AR(1) Processes.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/01677152\/79\/19\" rel='nofollow'>Statistics and Probability Letters<\/a> 79(19), pp. 2012-2019, 2009.<\/li>\n\n\n\n<li><strong>Wei\u00df (2009f)<\/strong><br>Wei\u00df, C.H.: Monitoring Correlated Processes with Binomial Marginals.<br><a href=\"http:\/\/www.informaworld.com\/smpp\/667597908-79715694\/title~content=g910509467~db=all\" rel='nofollow'>Journal of Applied Statistics<\/a> 36(4), pp. 399-414, 2009.<\/li>\n\n\n\n<li><strong>Wei\u00df (2009e)<\/strong><br>Wei\u00df, C.H.: Wolfram Research, Inc.: Mathematica, Version 7.<br>Software report, Computational Statistics &amp; Data Analysis Statistical Software Newsletter, 2009.<\/li>\n\n\n\n<li><strong>Wei\u00df (2009d)<\/strong><br>Wei\u00df, C.H.: Properties of a class of binary ARMA models.<br><a href=\"http:\/\/www.informaworld.com\/smpp\/667597908-72949978\/title~db=all~content=g909678580~tab=toc\" rel='nofollow'>Statistics: A Journal of Theoretical and Applied Statistics<\/a> 43(2), pp. 131-138, 2009.<\/li>\n\n\n\n<li><strong>Wei\u00df (2009c)<\/strong><br>Wei\u00df, C.H.: EWMA Monitoring of Correlated Processes of Poisson Counts.<br><a href=\"http:\/\/tandfonline.com\/toc\/ttqm20\/6\/2\" rel='nofollow'>Quality Technology and Quantitative Management<\/a> 6(2), pp. 137-153, 2009.<\/li>\n\n\n\n<li><strong>Wei\u00df (2009b)<\/strong><br>Wei\u00df, C.H.: Group Inspection of Dependent Binary Processes.<br><a href=\"http:\/\/www3.interscience.wiley.com\/journal\/121684789\/issue\" rel='nofollow'>Quality Reliability Engineering International<\/a> 25(2), pp. 151-165, 2009.<\/li>\n\n\n\n<li><strong>Wei\u00df (2009a)<\/strong><br>Wei\u00df, C.H.: A New Class of Autoregressive Models for Time Series of Binomial Counts.<br><a href=\"http:\/\/www.informaworld.com\/smpp\/667597908-42855348\/title~content=g907430188~db=all\" rel='nofollow'>Communications in Statistics &#8211; Theory and Methods<\/a> 38(4), pp. 447-460, 2009.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2008<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Wei\u00df (2008e)<\/strong><br>Wei\u00df, C.H.: The Combined INAR(p) Models for Time Series of Counts.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/01677152\/78\/13\" rel='nofollow'>Statistics and Probability Letters<\/a> 78(13), pp. 1817-1822, 2008.<\/li>\n\n\n\n<li><strong>Wei\u00df (2008d)<\/strong><br>Wei\u00df, C.H.: Thinning Operations for Modeling Time Series of Counts &#8211; A Survey.<br><a href=\"http:\/\/link.springer.com\/journal\/10182\/92\/3\/page\/1\" rel='nofollow'>Advances in Statistical Analysis<\/a> 92(3), pp. 319-341, 2008.<\/li>\n\n\n\n<li><strong>Wei\u00df (2008c)<\/strong><br>Wei\u00df, C.H.: Serial dependence and regression of Poisson INARMA models.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/03783758\/138\/10\" rel='nofollow'>Journal of Statistical Planning and Inference<\/a> 138(10), pp. 2975-2990, 2008.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; G\u00f6b (2008b)<\/strong><br>Wei\u00df, C.H., G\u00f6b, R.: Discovering Patterns in Categorical Time Series using IFS.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/01679473\/52\/9\" rel='nofollow'>Computational Statistics and Data Analysis<\/a> 52(9), pp. 4369-4379, 2008.<\/li>\n\n\n\n<li><strong>Wei\u00df &amp; G\u00f6b (2008a)<\/strong><br>Wei\u00df, C.H., G\u00f6b, R.: Measuring serial dependence in categorical time series.<br><a href=\"http:\/\/link.springer.com\/journal\/10182\/92\/1\/page\/1\" rel='nofollow'>Advances in Statistical Analysis<\/a> 92(1), pp. 71-89, 2008.<\/li>\n\n\n\n<li><strong>Wei\u00df (2008b)<\/strong><br>Wei\u00df, C.H.: Statistical Mining of Interesting Association Rules.<br><a href=\"http:\/\/link.springer.com\/journal\/11222\/18\/2\/page\/1\" rel='nofollow'>Statistics and Computing<\/a> 18(2), pp. 185-194, 2008.<\/li>\n\n\n\n<li><strong>Wei\u00df (2008a)<\/strong><br>Wei\u00df, C.H.: Visual analysis of categorical time series.<br><a href=\"http:\/\/www.sciencedirect.com\/science\/journal\/15723127\/5\/1\" rel='nofollow'>Statistical Methodology<\/a> 5(1), pp. 56-71, 2008.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2007<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Wei\u00df (2007d)<\/strong><br>Wei\u00df, C.H.: StatSoft, Inc., Tulsa, OK.: STATISTICA, Version 8.<br>Software review, <a href=\"http:\/\/link.springer.com\/journal\/10182\/91\/3\/page\/1\" rel='nofollow'>Advances in Statistical Analysis<\/a> 91(3), pp. 339-341, 2007.<\/li>\n\n\n\n<li><strong>Wei\u00df (2007c)<\/strong><br>Wei\u00df, C.H.: Sampling in Data Mining.<br>In Ruggeri et al. (Eds.): <a href=\"http:\/\/eu.wiley.com\/WileyCDA\/WileyTitle\/productCd-0470018615.html\" rel='nofollow'>Encyclopedia of Statistics in Quality and Reliability<\/a>, John Wiley &amp; Sons Ltd, pp. 1719-1722, 2007.<\/li>\n\n\n\n<li><strong>Wei\u00df (2007b)<\/strong><br>Wei\u00df, C.H.: Controlling Correlated Processes of Poisson Counts.<br><a href=\"http:\/\/www3.interscience.wiley.com\/cgi-bin\/jissue\/116322033\" rel='nofollow'>Quality Reliability Engineering International<\/a> 23(6), pp. 741-754, 2007.<\/li>\n\n\n\n<li><strong>Wei\u00df (2007a)<\/strong><br>Wei\u00df, C.H.: Zufall als Werkzeug &#8212; Monte-Carlo-Methoden in der Kunst.<br>In Lauter, M., Weigand, H.-G. ( <abbr title=\"Herausgeber\">Hrsg.<\/abbr>): Ausgerechnet &#8230; Mathematik und Konkrete Kunst, S. 57-59 und S. 160. <a href=\"http:\/\/www.spurbuch.de\/de\/produktleser-kunst\/product\/ausgerechnet.html\" rel='nofollow'>Spurbuchverlag<\/a>, Baunach, 2007.<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"talks\">Vortr\u00e4ge<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">2026<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>M\u00e4rz 2026<\/strong><br>Transcripts and Algebraic Distances in Time Series: Stochastic Properties and Nonparametric Dependence Tests.<br>Invited talk (20.03.2026), 16th Workshop on Stochastic Models and Their Applications, W\u00fcrzburg, 18. &#8211; 20. M\u00e4rz, 2026. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2026\/03\/Folien_03_26.pdf\">Folien_03_26.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2025<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2025<\/strong><br>Tobit models for count time series.<br>Statistische Woche 2025, Wiesbaden, 2. &#8211; 5. September, 2025. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2025\/08\/Folien_09_25.pdf\">Folien_09_25.pdf<\/a>)<\/li>\n\n\n\n<li><strong>April 2025<\/strong><br>Non-parametric Monitoring of Spatial Dependence.<br>Invited talk, Workshop on \u201cClassical ordinal patterns and beyond\u201d (COPAB25), University of Twente, 7. &#8211; 9. April, 2025. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2025\/03\/Folien_04_25.pdf\">Folien_04_25.pdf<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2025<\/strong><br>Coherent Forecasting of Ordinal Time Series.<br>DAGStat-Tagung 2025: Siebte gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, HU Berlin, 24. &#8211; 28. M\u00e4rz, 2025. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2025\/03\/Folien_03_25_2.pdf\">Folien_03_25_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2025<\/strong><br>Weighted Discrete ARMA Models for Categorical Time Series.<br>German Probability and Statistics Days 2025 (Stochastik-Tage 2025), Dresden, 11. &#8211; 14. M\u00e4rz, 2025. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2025\/03\/Folien_03_25_1.pdf\">Folien_03_25_1.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2024<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2024<\/strong><br>Non-parametric Tests for Spatial Dependence.<br>Invited talk, Statistical Modeling with Applications 2024 (StatMod2024), Belgrade, 24. &#8211; 25. September, 2024. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2024\/09\/Folien_09_24_3.pdf\">Folien_09_24_3.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2024<\/strong><br>Omnibus Control Charts for Poisson Counts.<br>24th Annual Conference of ENBIS, Leuven, 16. &#8211; 18. September, 2024. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2024\/09\/Folien_09_24_2.pdf\">Folien_09_24_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2024<\/strong><br>Hidden-Markov Models for Ordinal Time Series.<br>Statistische Woche 2024, Regensburg, 10. &#8211; 13. September, 2024. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2024\/09\/Folien_09_24_1.pdf\">Folien_09_24_1.pdf<\/a>)<\/li>\n\n\n\n<li><strong>August 2024<\/strong><br>Testing for Serial Dependence by Using Ordinal Patterns.<br>Invited talk, Bernoulli-ims 11th World Congress in Probability and Statistics, Bochum, 12. &#8211; 16. August, 2024. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2024\/07\/Folien_08_24.pdf\">Folien_08_24.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Mai 2024<\/strong><br>Anomaly Detection in Ordinal Quality-Related Processes by Control Charts.<br>ENBIS Spring Meeting 2024, Dortmund, 15. &#8211; 16. Mai, 2024. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2024\/05\/Folien_05_24.pdf\">Folien_05_24.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Mai 2024<\/strong><br>Non-parametric Control Charts for Monitoring Serial Dependence based on Ordinal Patterns.<br>Invited talk (14.05.2024), Oberseminar Stochastik, Universit\u00e4t Siegen.<\/li>\n\n\n\n<li><strong>M\u00e4rz 2024<\/strong><br>Using Spatial Ordinal Patterns for Non-parametric Testing of Spatial Dependence.<br>Invited talk (14.03.2024), 15th Workshop on Stochastic Models and Their Applications, Delft, 13. &#8211; 15. M\u00e4rz, 2024. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2024\/02\/Folien_03_24.pdf\">Folien_03_24.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Januar 2024<\/strong><br>Testing for Dependence by Using Ordinal Patterns: an Introduction.<br>Invited talk (24.01.2024), Statistisches Kolloquium, <abbr title=\"Technische Universit\u00e4t\">TU<\/abbr> Dortmund.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2023<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2023<\/strong><br>Multiplicative Error Models for Count Time Series.<br>Statistische Woche 2023, Dortmund, 11. &#8211; 13. September, 2023. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2023\/09\/Folien_09_23.pdf\">Folien_09_23.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Juli 2023<\/strong><br>Ordinal Compositional Data and Time Series.<br>37th International Workshop on Statistical Modelling (IWSM 2023), Dortmund, 17. &#8211; 21. Juli, 2023. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2023\/07\/Folien_07_23.pdf\">Folien_07_23.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Mai 2023<\/strong><br>Stein EWMA Control Charts for Count Processes.<br>Invited talk, Conference of the Greek Statistical Institute (GSI), 25. &#8211; 28. Mai, 2023. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2023\/05\/Folien_05_23.pdf\">Folien_05_23.pdf<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2023<\/strong><br>Optimal Stein-type Goodness-of-Fit Tests for Count Data.<br>German Probability and Statistics Days 2023 (Stochastik-Tage 2023), Essen, 7. &#8211; 10. M\u00e4rz, 2023. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2023\/03\/Folien_03_23.pdf\">Folien_03_23.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2022<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Dezember 2022<\/strong><br>An Introduction to Categorical Time Series Analysis.<br>Invited talk (21.12.2022), Colloquium, Institute for Mathematics and Applied Informatics, University of Hildesheim.<\/li>\n\n\n\n<li><strong>September 2022<\/strong><br>Non-parametric Monitoring of Serial Dependence based on Ordinal Patterns.<br>Statistische Woche 2022, M\u00fcnster, 20. &#8211; 23. September, 2022. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2022\/09\/Folien_09_22.pdf\">Folien_09_22.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Juli 2022<\/strong><br>Approximately Linear INGARCH Models for Spatio-Temporal Counts.<br>Invited talk (06.07.2022), 3rd LmB Conference on Multivariate Statistical Models: Count and Semi-Continuous, Universit\u00e9 de Franche-Comt\u00e9 in Besan\u00e7on, France, 06. Juli &#8211; 08. Juli, 2022. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2022\/06\/Folien_07_22.pdf\">Folien_07_22.pdf<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2022<\/strong><br>Approximately Linear INGARCH Models for Spatio-Temporal Counts.<br>DAGStat-Tagung 2022: Sechste gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universit\u00e4t Hamburg, 29. M\u00e4rz &#8211; 1. April, 2022. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2022\/03\/Folien_03_22_2.pdf\">Folien_03_22_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2022<\/strong><br>An Introduction to Categorical Time Series Analysis.<br>Invited talk (18.03.2022), Statistics seminar, Department of Mathematics and Statistics, University of Jyv\u00e4skyl\u00e4.<\/li>\n\n\n\n<li><strong>M\u00e4rz 2022<\/strong><br>Measuring Dispersion and Serial Dependence in Ordinal Time Series based on the Cumulative Paired \u03d5-Entropy.<br>Invited talk, Workshop on \u201cOrdinal methods: Concepts, applications, new developments and challenges\u201d (ORPATT22), MPI-PKS in Dresden, 28. Februar &#8211; 4. M\u00e4rz, 2022. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2022\/02\/Folien_03_22_1.pdf\">Folien_03_22_1.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2021<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2021<\/strong><br>Some goodness-of-fit tests for the Poisson distribution with applications in Biodosimetry.<br>German Probability and Statistics Days 2021 (Stochastik-Tage 2021), Mannheim, 27. September &#8211; 1. Oktober, 2021. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2021\/08\/Folien_09_21_4.pdf\">Folien_09_21_4.pdf<\/a>, <a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2021\/08\/Christian_H_Weiss_GPSD-2021.mp4\">video<\/a>)<\/li>\n\n\n\n<li><strong>September 2021<\/strong><br>Soft-clipping INGARCH Models for Time Series of Bounded Counts.<br>Statistische Woche 2021, 14. &#8211; 17. September, 2021. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2021\/09\/Folien_09_21_3.pdf\">Folien_09_21_3.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2021<\/strong><br>Analyzing categorical time series in the presence of missing observations.<br>21th Annual Conference of ENBIS (Online Conference), 13. &#8211; 15. September, 2021. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2021\/09\/Folien_09_21_2.pdf\">Folien_09_21_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2021<\/strong><br>On Approaches for Monitoring Categorical Event Series.<br>Keynote talk, 22nd European Young Statisticians Meeting (EYSM 2021), Panteion University Athens, 6. &#8211; 10. September, 2021. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2021\/08\/Folien_09_21_1.pdf\">Folien_09_21_1.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Juli 2021<\/strong><br>On PMF-Forecasting for Count Processes.<br>Plenary talk (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2021\/06\/PlenaryTalk_ChristianWeiss.mp4\">video<\/a>), 7th International conference on Time Series and Forecasting (ITISE 2021), Granada, 19. &#8211; 21. Juli, 2021. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2021\/06\/Folien_07_21.pdf\">Folien_07_21.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Mai 2021<\/strong><br>Efficient Accounting for Estimation Uncertainty in Coherent Forecasting of Count Processes.<br>ENBIS 2021 Spring Meeting, Newcastle, 17. &#8211; 18. Mai, 2021. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2021\/05\/Folien_05_21.pdf\">Folien_05_21.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2020<\/h3>\n\n\n\n<p>Aufgrund der Corona-Krise mussten alle bis dato f\u00fcr 2020 geplanten Vortr\u00e4ge abgesagt werden.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2019<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2019<\/strong><br>Time Series Modeling for Categorical Data.<br>Invited lecture, 2nd Dortmund-Bielefeld Summer School on Modern Topics in Time Series Analysis, University of Bielefeld, 10. September, 2019. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/lehre\/spezielle-veranstaltungen\/\">Details<\/a>)<\/li>\n\n\n\n<li><strong>September 2019<\/strong><br>Evaluating Approximate Point Forecasting of Count Processes.<br>19th Annual Conference of ENBIS, Budapest, 2. &#8211; 4. September, 2019. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2019\/08\/Folien_09_19.pdf\">Folien_09_19.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Juni 2019<\/strong><br>Discrete-Valued Time Series.<br>Invited lecture, XIII Summer School in Statistics UPC-UB 2019 at the Universitat Polit\u00e8cnica de Catalunya in Barcelona, 25.-28. Juni, 2019. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/lehre\/spezielle-veranstaltungen\/\">Details<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2019<\/strong><br>Distance-based Analysis of Ordinal Time Series.<br>DAGStat-Tagung 2019: Statistik unter einem Dach, F\u00fcnfte gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, LMU M\u00fcnchen, 19. &#8211; 22. M\u00e4rz, 2019. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2019\/03\/Folien_03_19_2.pdf\">Folien_03_19_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2019<\/strong><br>Generalized Discrete ARMA Models.<br>Invited talk (07.03.2019), 14th Workshop on Stochastic Models and Their Applications, Dresden, 6. &#8211; 8. M\u00e4rz, 2019. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2019\/02\/Folien_03_19_1.pdf\">Folien_03_19_1.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2018<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>November 2018<\/strong><br>SPC methods for time-dependent processes of counts.<br>Invited talk (29.11.2018), Forschungsseminar des Lehrstuhls f\u00fcr Quantitative Methoden, <abbr title=\"insbesondere\">insb.<\/abbr> Statistik, Europa-Universit\u00e4t Viadrina Frankfurt\/Oder.<\/li>\n\n\n\n<li><strong>November 2018<\/strong><br>An Introduction to Count Time Series Analysis.<br>Invited talk (27.11.2018), Kolloquium \u00fcber Mathematische Statistik und Stochastische Prozesse, Universit\u00e4t Hamburg.<\/li>\n\n\n\n<li><strong>November 2018<\/strong><br>Distance-based Analysis of Ordinal Data and Ordinal Time Series.<br>Invited talk (21.11.2018), Statistisches Seminar des Lehrstuhls f\u00fcr Statistik und \u00d6konometrie, FAU N\u00fcrnberg.<\/li>\n\n\n\n<li><strong>September 2018<\/strong><br>A Short Course in Categorical Time Series Analysis.<br>Invited lecture, Department of Quantitative and Computing Methods, Universidad Polit\u00e9cnica de Cartagena, 11.-12. September, 2018. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/lehre\/spezielle-veranstaltungen\/\">Details<\/a>)<\/li>\n\n\n\n<li><strong>September 2018<\/strong><br>Using Risk Metrics for Performance Evaluation of Control Charts.<br>18th Annual Conference of ENBIS, Nancy, 3. &#8211; 5. September, 2018. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2018\/08\/Folien_09_18.pdf\">Folien_09_18.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Juli 2018<\/strong><br>Model diagnostics for Poisson INARMA processes using bivariate dispersion indexes.<br>Invited talk (04.07.2018), The LmB Conferences on Multivariate Count Analysis, Universit\u00e9 de Franche-Comt\u00e9 in Besan\u00e7on, France, 04. Juli &#8211; 06. Juli, 2018. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2018\/06\/Folien_07_18.pdf\">Folien_07_18.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Juni 2018<\/strong><br>An Introduction to Count Time Series Analysis.<br>Invited talk (21.06.2018), Oberseminar des Instituts f\u00fcr Mathematische Stochastik, <abbr title=\"Technische Universit\u00e4t\">TU<\/abbr> Braunschweig.<\/li>\n\n\n\n<li><strong>April 2018<\/strong><br>An Introduction to Count Time Series Analysis with Applications in Economics.<br>Invited talk (25.04.2018), \u00d6konomisches Forschungsseminar, WWU M\u00fcnster.<\/li>\n\n\n\n<li><strong>Februar 2018<\/strong><br>On Eigenvalues of the Transition Matrix of some Count-Data Markov Chains.<br>13th German Probability and Statistics Days 2018 (Stochastik-Tage 2018), Freiburg, 27. Februar &#8211; 02. M\u00e4rz, 2018. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2018\/02\/Folien_02_18.pdf\">Folien_02_18.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2017<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Dezember 2017<br><\/strong>Analysis and Modeling of Categorical Time Series: Difficulties and Possible Solutions.<br>Invited talk (07.12.2017), Kolloquium, Institut f\u00fcr Mathematik, Universit\u00e4t zu L\u00fcbeck.<\/li>\n\n\n\n<li><strong>September 2017<\/strong><br>Guaranteed Conditional ARL Performance in the Presence of Autocorrelation.<br>Statistische Woche, Jahrestagung 2017, Rostock, 19. &#8211; 22. September, 2017. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_17_2.pdf\">Folien_09_17_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2017<\/strong><br>Goodness-of-Fit Testing for Count Time Series.<br>Invited talk (10.09.2017), 3rd Workshop on Goodness-of-fit and Change-Point Problems, Bad Herrenalb, 8. &#8211; 10. Septempter, 2017. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_17_1.pdf\">Folien_09_17_1.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Februar 2017<\/strong><br>Testing the Compounding Structure of the CP-INARCH Model.<br>13th Workshop on Stochastic Models and Their Applications, Berlin, 20. &#8211; 24. Februar, 2017. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_02_17.pdf\">Folien_02_17.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2016<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>November 2016<\/strong><br>Analyse und Modellierung von Z\u00e4hldatenzeitreihen mit Anwendungen im Verkehrswesen.<br>Invited talk (29.11.2016), Brown Bag Seminar, <abbr title=\"Technische Universit\u00e4t\">TU<\/abbr> Dresden.<\/li>\n\n\n\n<li><strong>November 2016<\/strong><br>Modeling and Analysis of Count Data Time Series: An Introduction.<br>Invited talk (09.11.2016), Uppsala Mathematics Colloquium, Department of Mathematics, Uppsala University.<\/li>\n\n\n\n<li><strong>September 2016<\/strong><br>Diagnostic Tests for Binomial AR(1) Processes.<br>Statistische Woche, Jahrestagung 2016, Augsburg, 13. &#8211; 16. September, 2016. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_16.pdf\">Folien_09_16.pdf<\/a>)<\/li>\n\n\n\n<li><strong>August 2016<\/strong><br>Control Charts for Time-Dependent Categorical Processes.<br>12th International Workshop on Intelligent Statistical Quality Control (ISQC 2016), Hamburg, August 16. &#8211; 19., 2016. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_08_16.pdf\">Folien_08_16.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Mai 2016<\/strong><br>On Eigenvalues of the Transition Matrix of some Count Data Markov Chains.<br>Invited talk (11.05.2016), CEMAT\u2019s Open Seminar and Probability and Statistics Seminar, Department of Mathematics of Instituto Superior T\u00e9cnico, Lisboa.<\/li>\n\n\n\n<li><strong>M\u00e4rz 2016<\/strong><br>SPC Methods for Time-Dependent Processes of Counts.<br>Poster-Pr\u00e4sentation, DAGStat-Tagung 2016: Statistik unter einem Dach, Vierte gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universit\u00e4t G\u00f6ttingen, 15. &#8211; 18. M\u00e4rz, 2016. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Poster_03_16.pdf\">Poster_03_16.pdf<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2016<\/strong><br>Introduction to Integer-Valued Time Series.<br>Invited lecture, Tutorial, DAGStat-Tagung 2016: Statistik unter einem Dach, Vierte gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universit\u00e4t G\u00f6ttingen, 14. M\u00e4rz, 2016. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/lehre\/spezielle-veranstaltungen\/\">Details<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2016<\/strong><br>Time Reversibility of INAR(1) Processes and Testing for Poisson Innovations.<br>12th German Probability and Statistics Days 2016 (Stochastik-Tage 2016), Bochum, 01. &#8211; 04. M\u00e4rz, 2016. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_03_16.pdf\">Folien_03_16.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2015<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Oktober 2015<\/strong><br>An Introduction to Categorical Time Series Analysis.<br>Invited talk, Research Seminar in Mathematical Econometrics, Stochastics and Finance (15.10.2015), Lehrstuhl f\u00fcr Statistik, Universit\u00e4t Mannheim.<\/li>\n\n\n\n<li><strong>September 2015<\/strong><br>Binomial Autoregressive Process with Density Dependent Thinning.<br>2015 NBER\/NSF Time Series Conference, Wien, 25. &#8211; 26. September, 2015. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_15_3.pdf\">Folien_09_15_3.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2015<\/strong><br>Analysis and Modelling of Categorical Time Series.<br>Poster-Pr\u00e4sentation, Statistische Woche, Jahrestagung 2015, Hamburg, 15. &#8211; 18. September, 2015. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Poster_09_15.pdf\">Poster_09_15.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2015<\/strong><br>Bias Corrections for Moment Estimators in Poisson INAR(1) and INARCH(1) Processes.<br>Statistische Woche, Jahrestagung 2015, Hamburg, 15. &#8211; 18. September, 2015. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_15_2.pdf\">Folien_09_15_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2015<\/strong><br>Newsvendor Model in Presence of Correlated Discrete Demand.<br>15th Annual Conference of ENBIS, Prag, 7. &#8211; 9. September, 2015. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_15_1.pdf\">Folien_09_15_1.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Februar 2015<\/strong><br>The Marginal Distribution of Compound Poisson INAR(1) Processes.<br>12th Workshop on Stochastic Models and Their Applications, Wroclaw, 17. &#8211; 20. Februar, 2015. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_02_15.pdf\">Folien_02_15.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Februar 2015<\/strong><br>Modeling and Analysis of Count Data Time Series: Recent Research Activities.<br>Invited talk (03.02.2015), Centre for Mathematics, University of Coimbra.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2014<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2014<\/strong><br>Integer-Valued Autoregressive Models for Counts Showing Underdispersion.<br>14th Annual Conference of ENBIS, Linz, 22. &#8211; 24. September, 2014. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_14_2.pdf\">Folien_09_14_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2014<\/strong><br>Binomial Models for Count Data Time Series with a Finite Range.<br>Poster-Pr\u00e4sentation, Statistische Woche, Jahrestagung 2014, Hannover, 16. &#8211; 19. September, 2014. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Poster_09_14.pdf\">Poster_09_14.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2014<\/strong><br>Serial Dependence in Categorical Time Series.<br>Statistische Woche, Jahrestagung 2014, Hannover, 16. &#8211; 19. September, 2014. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_14_1.pdf\">Folien_09_14_1.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Juli 2014<\/strong><br>Zur Er\u00f6ffnung der Ausstellung &#8222;Fraktale Stadtansichten&#8220; von Hiltrud Heinrich.<br>Laudatio (06.07.2014), Vernissage in der Galerie &#8222;ART Bessungen&#8220;, Darmstadt.<\/li>\n\n\n\n<li><strong>Juli 2014<\/strong><br>Diagnosing Overdispersion in Count Data Time Series.<br>Invited talk (02.07.2014), Workshop &#8222;Count Data Modeling and Analysis&#8220;, LMB trimesters, Universit\u00e9 de Franche-Comt\u00e9 in Besan\u00e7on, France, 30. Juni &#8211; 04. Juli, 2014. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_07_14.pdf\">Folien_07_14.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Juni 2014<\/strong><br>An Introduction to Integer-Valued Time Series Models.<br>Invited lecture (30.06.2014), Mini-course &#8222;Integer-Valued Time Series Models&#8220;, LMB trimesters, Universit\u00e9 de Franche-Comt\u00e9 in Besan\u00e7on, France, 30. Juni &#8211; 04. Juli, 2014. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/lehre\/spezielle-veranstaltungen\/\">Details<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2014<\/strong><br>Bivariate Binomial Autoregressive Models.<br>11th German Probability and Statistics Days 2014 (Stochastik-Tage 2014), Ulm, 04. &#8211; 07. M\u00e4rz, 2014. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_03_14.pdf\">Folien_03_14.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2013<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2013<\/strong><br>Phase-I Analysis of Time-Dependent Counts with Missing Observations.<br>13th Annual Conference of ENBIS, Ankara, 16. &#8211; 18. September, 2013. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_13.pdf\">Folien_09_13.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Mai 2013<\/strong><br>Mathematikausbildung f\u00fcr INT-Studierende an der <abbr title=\"Technische Universit\u00e4t\">TU<\/abbr> Darmstadt &#8211; Erfahrungen und neue Konzepte.<br>Keynote Lecture (28.05.2013), Workshop &#8222;Eine Woche Zeit &#8211; Wege aus der MINT-Schw\u00e4che: Neue inhaltliche und didaktische Konzepte f\u00fcr die universit\u00e4re Mathematik-Ausbildung&#8220;, Gut Siggen, 27. Mai &#8211; 1. Juni, 2013.<\/li>\n\n\n\n<li><strong>M\u00e4rz 2013<\/strong><br>Residuals-based CUSUM Charts for Poisson INAR(1) Processes.<br>DAGStat-Tagung 2013: Statistik unter einem Dach, Dritte gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universit\u00e4t Freiburg, 19. &#8211; 22. M\u00e4rz, 2013. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_03_13_2.pdf\">Folien_03_13_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2013<\/strong><br>Diagnosing and Modelling Extra-Binomial Variation for Time-Dependent Counts.<br>DAGStat-Tagung 2013: Statistik unter einem Dach, Dritte gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universit\u00e4t Freiburg, 19. &#8211; 22. M\u00e4rz, 2013. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_03_13_1.pdf\">Folien_03_13_1.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Februar 2013<\/strong><br>Compound Poisson INAR(1) Processes: Stochastic Properties and Testing for Overdispersion.<br>11th Workshop on Stochastic Models and Their Applications, Hamburg, 20. &#8211; 22. Februar, 2013. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_02_13.pdf\">Folien_02_13.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2012<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2012<\/strong><br>Modeling and Analysis of Count Data Time Series: Recent Research Activities.<br>Invited talk (25.09.2012), Mathematics Department, University of Aveiro.<\/li>\n\n\n\n<li><strong>September 2012<\/strong><br>Chain Binomial Models and Binomial Autoregressive Processes.<br>Statistische Woche, Jahrestagung 2012, Wien, 18. &#8211; 21. September, 2012. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_12_2.pdf\">Folien_09_12_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2012<\/strong><br>Detection of Abrupt Changes in Count Data Time Series: Cumulative Sum Derivations for INARCH(1) Models<br>Twelvth Annual Conference of ENBIS, Ljubljana, 10. &#8211; 12. September, 2012. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_12_1.pdf\">Folien_09_12_1.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2011<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>November 2011<\/strong><br>Analyse und Modellierung von Z\u00e4hldatenzeitreihen.<br>Invited talk, Forschungsseminar des Lehrstuhls f\u00fcr Statistik (10.11.2011), Universit\u00e4t Augsburg.<\/li>\n\n\n\n<li><strong>Oktober 2011<\/strong><br>Ein erweitertes Poisson INAR(1)-Modell<br>Invited talk, Workshop des Zentrums f\u00fcr Statistik der <abbr title=\"Technische Universit\u00e4t\">TU<\/abbr> Darmstadt, Grasellenbach, 05. &#8211; 06. Oktober, 2011. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_10_11.pdf\">Folien_10_11.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2011<\/strong><br>Empirical Measures of Signed Serial Dependence in Categorical Time Series.<br>Statistische Woche, Jahrestagung 2011, Leipzig, 20. &#8211; 23. September, 2011. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_11_2.pdf\">Folien_09_11_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2011<\/strong><br>Categorical Time Series: Analysis, Modelling, Monitoring?<br>Invited talk (<a href=\"http:\/\/www.enbis.org\/awards\/young_statisitician\/past_recipients?_ts=1\" rel='nofollow'>Young Statistician&#8217;s Award<\/a>), Eleventh Annual Conference of ENBIS, Coimbra, 05. &#8211; 07. September, 2011. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_11_1.pdf\">Folien_09_11_1.pdf<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2011<\/strong><br>Continuously Monitoring Categorical Processes.<br>10th Workshop on Stochastic Models and Their Applications, Wismar, 01. &#8211; 04. M\u00e4rz, 2011. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_03_11.pdf\">Folien_03_11.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2010<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2010<\/strong><br>Process Capability Analysis for Serially Dependent Processes of Poisson Counts.<br>Invited talk, Tenth Annual Conference of ENBIS, Antwerpen, 13. &#8211; 15. September, 2010. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_10.pdf\">Folien_09_10.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Juni 2010<\/strong><br>AR(1)-Modelle f\u00fcr Z\u00e4hldatenzeitreihen.<br>Invited talk, Kolloquium der F\u00e4chergruppe Mathematik und Statistik (21.06.2010), Helmut-Schmidt-Universit\u00e4t Hamburg.<\/li>\n\n\n\n<li><strong>M\u00e4rz 2010<\/strong><br>Detecting Mean Increases in Poisson INAR(1) Processes with EWMA Control Charts.<br>DAGStat-Tagung 2010: Statistik unter einem Dach, Zweite gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, <abbr title=\"Technische Universit\u00e4t\">TU<\/abbr> Dortmund, 23. &#8211; 26. M\u00e4rz, 2010. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_03_10.pdf\">Folien_03_10.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2009<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Oktober 2009<\/strong><br>The INARCH(1) Model for Overdispersed Time Series of Counts.<br>Statistische Woche, Jahrestagung 2009, Wuppertal, 5. &#8211; 8. Oktober, 2009. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_10_09.pdf\">Folien_10_09.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2009<\/strong><br>EWMA Control Charts for Monitoring Binary Processes with Applications to Medical Diagnosis Data.<br>Ninth Annual Conference of ENBIS, G\u00f6teburg, 21. &#8211; 23. September, 2009. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_09.pdf\">Folien_09_09.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Juni 2009<\/strong><br>Statistische Kontrolle von Z\u00e4hldatenprozessen mit \u00dcberdispersion.<br>Pfingsttagung der Deutschen Statistischen Gesellschaft, Merseburg, 04. &#8211; 05. Juni, 2009. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_06_09.pdf\">Folien_06_09.pdf<\/a>)<\/li>\n\n\n\n<li><strong>April 2009<\/strong><br>Modellierung und Kontrolle von Z\u00e4hldatenprozessen.<br>Invited talk, Dresdner Kolloquium zur Stochastik (14.04.2009), Institut f\u00fcr Mathematische Stochastik, Technische Universit\u00e4t Dresden.<\/li>\n\n\n\n<li><strong>M\u00e4rz 2009<\/strong><br>CUSUM Monitoring of First-Order Integer-Valued Autoregressive Processes of Poisson Counts.<br>9th Workshop on Stochastic Models and Their Applications, Aachen, 03. &#8211; 06. M\u00e4rz, 2009. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_03_09.pdf\">Folien_03_09.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2008<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Dezember 2008<\/strong><br>Modeling and Control of Count Data Processes.<br>Invited talk, Forschungsseminar (02.12.2008), Lehrstuhl f\u00fcr Quantitative Methoden, <abbr title=\"insbesondere\">insb.<\/abbr> Statistik, Europa-Universit\u00e4t Viadrina Frankfurt (Oder).<\/li>\n\n\n\n<li><strong>November 2008<\/strong><br>Modeling and Control of Count Data Processes.<br>Invited talk, Oberseminar Stochastik (20.11.2008), Fakult\u00e4t f\u00fcr Mathematik, Otto-von-Guericke-Universit\u00e4t Magdeburg.<\/li>\n\n\n\n<li><strong>September 2008<\/strong><br>Group Inspection of Dependent Binary Processes.<br>Eighth Annual Meeting of ENBIS, Athen, 22. &#8211; 24. September, 2008. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_08_2.pdf\">Folien_09_08_2.pdf<\/a>)<\/li>\n\n\n\n<li><strong>September 2008<\/strong><br>Controlling Jumps in Poisson INAR(1) Processes.<br>Statistische Woche, Jahrestagung 2008, K\u00f6ln, 15. &#8211; 18. September, 2008. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_08_1.pdf\">Folien_09_08_1.pdf<\/a>)<\/li>\n\n\n\n<li><strong>August 2008<\/strong><br>Commercial meets Open Source &#8211; Tuning STATISTICA with R.<br>useR! &#8211; The R User Conference 2008, Dortmund, 12. &#8211; 14. August, 2008. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_08_08.pdf\">Folien_08_08.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Mai 2008<\/strong><br>EWMA-Kontrollkarten f\u00fcr korrelierte Z\u00e4hldatenprozesse mit Poisson-Randverteilung.<br>Pfingsttagung der Deutschen Statistischen Gesellschaft, Berlin, 14. &#8211; 16. Mai, 2008. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_05_08.pdf\">Folien_05_08.pdf<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2008<\/strong><br>A New Class of Autoregressive Models for Time Series of Binomial Counts.<br>8th German Open Conference on Probability and Statistics (GOCPS 2008, &#8222;Aachener Stochastik-Tage&#8220;), Aachen, 04. &#8211; 07. M\u00e4rz, 2008. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_03_08.pdf\">Folien_03_08.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2007<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2007<\/strong><br>Controlling Correlated Processes with Binomial Marginals.<br>Seventh Annual Meeting of ENBIS, Dortmund, 24. &#8211; 26. September, 2007. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_07.pdf\">Folien_09_07.pdf<\/a>)<\/li>\n\n\n\n<li><strong>April 2007<\/strong><br>Zufall als Werkzeug &#8211; Monte-Carlo-Methoden in der Kunst.<br>Ausgerechnet &#8230; Mathematik und Konkrete Kunst, Nacht der Mathematik, Kulturspeicher W\u00fcrzburg, 26. April, 2007.<\/li>\n\n\n\n<li><strong>M\u00e4rz 2007<\/strong><br>Visual Analysis of Categorical Time Series.<br>DAGStat-Tagung 2007: Statistik unter einem Dach, Erste gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universit\u00e4t Bielefeld, 27. &#8211; 30. M\u00e4rz, 2007. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_03_07.pdf\">Folien_03_07.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2006<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2006<\/strong><br>Controlling Correlated Processes of Poisson Counts.<br>Sixth Annual Meeting of ENBIS, Breslau, Polen, 18. &#8211; 20. September, 2006. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_06.pdf\">Folien_09_06.pdf<\/a>)<\/li>\n\n\n\n<li><strong>Juni 2006<\/strong><br>Measuring Serial Dependence in Categorical Time Series.<br>Pfingsttagung der Deutschen Statistischen Gesellschaft, Helmut-Schmidt-Universit\u00e4t, Hamburg, 07. &#8211; 09. Juni, 2006. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_06_06.pdf\">Folien_06_06.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2005<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>September 2005<\/strong><br>Discover Patterns in Categorical Time Series using IFS.<br>Fifth Annual Meeting of ENBIS, Newcastle, UK, 14. &#8211; 16. September, 2005. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_09_05.pdf\">Folien_09_05.pdf<\/a>)<\/li>\n\n\n\n<li><strong>M\u00e4rz 2005<\/strong><br>Sequential Pattern Analysis und Markov-Modelle.<br>7. Workshop Stochastische Modelle und ihre Anwendungen, W\u00fcrzburg, Sch\u00f6nstattzentrum Marienh\u00f6he, 7. &#8211; 10. M\u00e4rz 2005. (<a href=\"https:\/\/www.hsu-hh.de\/mathstat\/wp-content\/uploads\/sites\/781\/2017\/10\/Folien_03_05.pdf\">Folien_03_05.pdf<\/a>)<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>B\u00fccher Artikel 2026 2025 2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 Vortr\u00e4ge 2026 2025 2024 2023 2022 2021 2020 [&hellip;]<\/p>\n","protected":false},"author":98,"featured_media":0,"parent":170,"menu_order":2,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-236","page","type-page","status-publish","hentry","category-forschung"],"_links":{"self":[{"href":"https:\/\/www.hsu-hh.de\/mathstat\/wp-json\/wp\/v2\/pages\/236","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.hsu-hh.de\/mathstat\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.hsu-hh.de\/mathstat\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.hsu-hh.de\/mathstat\/wp-json\/wp\/v2\/users\/98"}],"replies":[{"embeddable":true,"href":"https:\/\/www.hsu-hh.de\/mathstat\/wp-json\/wp\/v2\/comments?post=236"}],"version-history":[{"count":398,"href":"https:\/\/www.hsu-hh.de\/mathstat\/wp-json\/wp\/v2\/pages\/236\/revisions"}],"predecessor-version":[{"id":2873,"href":"https:\/\/www.hsu-hh.de\/mathstat\/wp-json\/wp\/v2\/pages\/236\/revisions\/2873"}],"up":[{"embeddable":true,"href":"https:\/\/www.hsu-hh.de\/mathstat\/wp-json\/wp\/v2\/pages\/170"}],"wp:attachment":[{"href":"https:\/\/www.hsu-hh.de\/mathstat\/wp-json\/wp\/v2\/media?parent=236"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.hsu-hh.de\/mathstat\/wp-json\/wp\/v2\/categories?post=236"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.hsu-hh.de\/mathstat\/wp-json\/wp\/v2\/tags?post=236"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}