Publications & Talks

 

9783036521213
Weiß, C.H. (Ed.):
Discrete-Valued Time Series.
Special Issue Reprint, Entropy, MDPI, Basel, 2024.
9783036521213
Weiß, C.H. (Ed.):
Time Series Modelling.
Special Issue Reprint, Entropy, MDPI, Basel, 2021.
9781119096962
Weiß, C.H.:
An Introduction to Discrete-Valued Time Series.
John Wiley & Sons, Inc, Chichester, 2018.
(Further information …)
9783110425222
Weiß, C.H.:
Mathematica und Wolfram Language
Einführung – Funktionsumfang – Praxisbeispiele.
De Gruyter Oldenbourg Verlag, Berlin, 2017.
(Further information …)
Handbuch Mathematica
Weiß, C.H.:
Mathematica und Wolfram Language – Eine Einführung.
RRZN Handbuch, 9., vollständig überarbeitete Auflage, Hannover, 2016.
(1. Auflage: 2007, 2. Auflage: 2008, 3. und 4. Auflage: 2010, 5.-7. Auflage: 2011, 8. Auflage: 2013)
(Further information …)
Dissertation
Weiß, C.H.:
Categorical Time Series Analysis and Applications in
Statistical Quality Control.
Dissertation (Fakultät für Mathematik und Informatik der Universität Würzburg), dissertation.de – Verlag, Berlin, 2009.
(Further information …)
Handbuch Statistica
Weiß, C.H.:
STATISTICA – Eine Einführung.
RRZN Handbuch, 3., aktualisierte Auflage, Hannover, 2009.
(1. Auflage: 2005, 2. Auflage: 2006)
(Further information …)
Mathematica kompakt
Weiß, C.H.:
Mathematica kompakt
Einführung – Funktionsumfang – Praxisbeispiele.
R. Oldenbourg Verlag, München, Wien, 2008.
(Further information …)
Statistica
Weiß, C.H.:
Datenanalyse und Modellierung mit STATISTICA.
R. Oldenbourg Verlag, München, Wien, 2006.
(Further information …)

 

 

2024

  • Weiß (2024)
    Weiß, C.H.: Stein EWMA Control Charts for Count Processes.
    Accepted for publication in Methods and Applications in Systems Assurance & Quality, Book Series “Advanced Research in Reliability and System Assurance”, CRC Press, 2024 (arXiv preprint).
  • Jahn & Weiß (2024)
    Jahn, M., Weiß, C.H.: Nonlinear GARCH-type models for ordinal time series.
    Stochastic Environmental Research and Risk Assessment 38(2), 637-649, 2024.
  • Jahn (2024)
    Jahn, M.: A flexible likelihood-based neural network extension of the classic spatio-temporal model.
    Spatial Statistics 59, 100801, 2024.
  • Wang & Weiß (2024)
    Wang, H., Weiß, C.H.: The Circumstance-driven Bivariate Integer-valued Autoregressive Model.
    Entropy 26(2), 168, 2024.
  • Weiß & Kim (2024)
    Weiß, C.H., Kim, H.-Y.: Using Spatial Ordinal Patterns for Non-parametric Testing of Spatial Dependence.
    Spatial Statistics 59, 100800, 2024.
  • Weiß & Zhu (2024)
    Weiß, C.H., Zhu, F.: Conditional-mean Multiplicative Operator Models for Count Time Series.
    Computational Statistics and Data Analysis 191, 107885, 2024.

 

2023

  • Jahn (2023)
    Jahn, M.: Artificial Neural Networks and Time Series of Counts: A Class of Nonlinear INGARCH Models.
    Accepted for publication in Studies in Nonlinear Dynamics & Econometrics, 2023.
  • Aleksandrov et al. (2023)
    Aleksandrov, B., Weiß, C.H., Nik, S., Faymonville, M., Jentsch, C.: Modelling and Diagnostic Tests for Poisson and Negative-binomial Count Time Series.
    Accepted for publication in Metrika, 2023.
  • Weiß (2023c)
    Weiß, C.H.: Ordinal compositional data and time series.
    Accepted for publication in Statistical Modelling, 2023.
  • Weiß & Schnurr (2023)
    Weiß, C.H., Schnurr, A.: Generalized ordinal patterns in discrete-valued time series: nonparametric testing for serial dependence.
    Accepted for publication in Journal of Nonparametric Statistics, 2023.
  • Weiß (2023b)
    Weiß, C.H.: Control Charts for Poisson Counts based on the Stein-Chen Identity.
    Accepted for publication in Advanced Statistical Methods in Statistical Process Monitoring, Finance, and Environmental Science, Springer, 2023 (arXiv preprint).
  • Yang et al. (2023)
    Yang, K., Zhao, X., Dong, X., Weiß, C.H.: Self-exciting hysteretic binomial autoregressive processes.
    Accepted for publication in Statistical Papers, 2023.
  • Martins et al. (2023)
    Martins, A., Scotto, M.G., Weiß, C.H., Gouveia, S.: Space-time integer-valued ARMA modelling for time series of counts.
    Electronic Journal of Statistics 17(2), 3472-3511, 2023.
  • Weiß (2023a)
    Weiß, C.H.: Discrete-Valued Time Series.
    Editorial, Entropy 25(12), 1576, 2023.
  • López-Oriona et al. (2023)
    López-Oriona, Á., Weiß, C.H., Vilar, J.A.: Two novel distances for ordinal time series and their application to fuzzy clustering.
    Fuzzy Sets and Systems 468, 108590, 2023.
  • Ottenstreuer et al. (2023)
    Ottenstreuer, S., Weiß, C.H., Testik, M.C.: A Review and Comparison of Control Charts for Ordinal Samples.
    Journal of Quality Technology 55(4), pp. 422-441, 2023.
  • Weiß & Testik (2023)
    Weiß, C.H., Testik, M.C.: Non-parametric Control Charts for Monitoring Serial Dependence based on Ordinal Patterns.
    Technometrics 65(3), pp. 340-350, 2023.
  • Faymonville et al. (2023)
    Faymonville, M., Jentsch, C., Weiß, C.H., Aleksandrov, B.: Semiparametric estimation of INAR models using roughness penalization.
    Statistical Methods and Applications 32(2), pp. 365-400, 2023.
  • Jahn et al. (2023)
    Jahn, M., Weiß, C.H., Kim, H.-Y.: Approximately Linear INGARCH Models for Spatio-Temporal Counts.
    Journal of the Royal Statistical Society (Series C) 72(2), pp. 476-497, 2023.
  • Wang & Weiß (2023)
    Wang, S., Weiß, C.H.: New Characterizations of the (Discrete) Lindley Distribution and their Applications.
    Mathematics and Computers in Simulation 212, pp. 310-322, 2023.
  • Homburg et al. (2023)
    Homburg, A., Weiß, C.H., Alwan, L.C., Frahm, G., Göb, R.: PMF-Forecasting for Count Processes: A Comprehensive Performance Analysis.
    Theory and Applications of Time Series Analysis and Forecasting: Selected Contributions from ITISE 2021, Contributions to Statistics, Springer, pp. 79-90, 2023.
  • Weiß et al. (2023b)
    Weiß, C.H., Puig, P., Aleksandrov, B.: Optimal Stein-type Goodness-of-Fit Tests for Count Data.
    Biometrical Journal 65(2), 2200073, 2023.
  • Yu et al. (2023)
    Yu, K., Wang, H., Weiß, C.H.: An Empirical-Likelihood-based Structural-Change Test for INAR Processes.
    Journal of Statistical Computation and Simulation 93(3), pp. 442-458, 2023.
  • Weiß et al. (2023a)
    Weiß, C.H., Aleksandrov, B., Faymonville, M., Jentsch, C.: Partial Autocorrelation Diagnostics for Count Time Series.
    Entropy 25(1), 105, Special Issue “Discrete-Valued Time Series”, 2023.

 

2022

  • Weiß & Jahn (2022)
    Weiß, C.H., Jahn, M.: Soft-clipping INGARCH models for time series of bounded counts.
    Accepted for publication in Statistical Modelling, 2022.
  • Weiß & Testik (2022)
    Weiß, C.H., Testik, M.C.: Monitoring Count Time Series: Robustness to Nonlinearity When Linear Models are Utilized.
    Quality and Reliability Engineering International 38(8), pp. 4356-4371, 2022.
  • Aleksandrov et al. (2022b)
    Aleksandrov, B., Weiß, C.H., Jentsch, C., Faymonville, M.: Novel Goodness-of-Fit Tests for Binomial Count Time Series.
    Statistics 56(5), pp. 957-990, 2022.
  • Weiß (2022b)
    Weiß, C.H.: Non-parametric Tests for Serial Dependence in Time Series based on Asymptotic Implementations of Ordinal-Pattern Statistics.
    Chaos: An Interdisciplinary Journal of Nonlinear Science 32(9), 093107, 2022.
    (Focus Issue “Ordinal Methods: Concepts, Applications, New Developments and Challenges”
  • Weiß et al. (2022c)
    Weiß, C.H., Homburg, A., Alwan, L.C., Frahm, G., Göb, R.: Efficient Accounting for Estimation Uncertainty in Coherent Forecasting of Count Processes.
    Journal of Applied Statistics 49(8), pp. 1957-1978, 2022.
  • Ottenstreuer (2022)
    Ottenstreuer, S.: The Shiryaev-Roberts Control Chart for Markovian Count Time Series.
    Quality and Reliability Engineering International 38(3), pp. 1207-1225, 2022.
  • Weiß et al. (2022b)
    Weiß, C.H., Zhu, F., Hoshiyar, A.: Softplus INGARCH Models.
    Statistica Sinica 32(2), pp. 1099-1120, 2022.
  • Nik & Weiß (2022)
    Nik, S., Weiß, C.H.: Smooth-Transition Autoregressive Models for Time Series of Bounded Counts.
    Stochastic Models 37(4), pp. 568-588, 2022.
  • Weiß & Aleksandrov (2022)
    Weiß, C.H., Aleksandrov, B.: Computing (Bivariate) Poisson Moments using Stein–Chen Identities.
    The American Statistician 76(1), pp. 10-15, 2022.
  • Weiß (2022a)
    Weiß, C.H.: Measuring Dispersion and Serial Dependence in Ordinal Time Series based on the Cumulative Paired ϕ-Entropy.
    Entropy 24(1), 42, 2022.
  • Aleksandrov et al. (2022a)
    Aleksandrov, B., Weiß, C.H., Jentsch, C.: Goodness-of-Fit Tests for Poisson Count Time Series based on the Stein-Chen Identity.
    Statistica Neerlandica 76(1), pp. 35-64, 2022.
  • Weiß et al. (2022a)
    Weiß, C.H., Ruiz Marín, M., Keller, K., Matilla-García, M.: Non-Parametric Analysis of Serial Dependence in Time Series using Ordinal Patterns.
    Computational Statistics and Data Analysis 168, 107381, 2022.

 

2021

 

2020

  • Homburg (2020)
    Homburg, A.: Criteria for Evaluating Approximations of Count Distributions.
    Communications in Statistics – Simulation and Computation 49(12), pp. 3152-3170, 2020.
  • Nik & Weiß (2020)
    Nik, S., Weiß, C.H.: CLAR(1) Point Forecasting under Estimation Uncertainty.
    Statistica Neerlandica 74(4), pp. 489-516, 2020.
  • Kim et al. (2020)
    Kim, H.-Y., Weiß, C.H., Möller, T.A.: Models for Autoregressive Processes of Bounded Counts: How Different Are They?.
    Computational Statistics 35(4), pp. 1715-1736, 2020.
  • Weiß (2020b)
    Weiß, C.H.: Distance-based Analysis of Ordinal Data and Ordinal Time Series.
    Journal of the American Statistical Association 115(531), pp. 1189-1200, 2020.
  • Aleksandrov & Weiß (2020b)
    Aleksandrov, B., Weiß, C.H.: Testing the Dispersion Structure of Count Time Series Using Pearson Residuals.
    AStA Advances in Statistical Analysis 104(3), pp. 325-361, 2020.
  • Möller & Weiß (2020)
    Möller, T.A., Weiß, C.H.: Generalized Discrete ARMA Models.
    Applied Stochastic Models in Business and Industry 36(4), pp. 641-659, 2020.
  • Oh & Weiß (2020)
    Oh, J., Weiß, C.H.: On the Individuals Chart with Supplementary Runs Rules under Serial Dependence.
    Methodology and Computing in Applied Probability 22(3), pp. 1257-1273, 2020.
  • Weiß et al. (2020)
    Weiß, C.H., Scherer, L., Aleksandrov, B., Feld, M.H.-J.M.: Checking Model Adequacy for Count Time Series by Using Pearson Residuals.
    Journal of Time Series Econometrics 12(1), 20180018, 2020.
  • Weiß (2020a)
    Weiß, C.H.: Regime-Switching Discrete ARMA Models for Categorical Time Series.
    Entropy 22(4), 458, 2020.
  • Atalay et al. (2020)
    Atalay, M., Testik, M.C., Duran, S., Weiß, C.H.: Guidelines for automating Phase I of control charts by considering effects on Phase-II performance of individuals control chart.
    Quality Engineering 32(2), pp. 223-243, 2020.
  • Weiß & Feld (2020)
    Weiß, C.H., Feld, M.H.-J.M.: On the Performance of Information Criteria for Model Identification of Count Time Series.
    Studies in Nonlinear Dynamics & Econometrics 24(1), 20180012, 2020.
  • Möller et al. (2020)
    Möller, T.A., Weiß, C.H., Kim, H.-Y.: Modeling Counts with State-Dependent Zero Inflation.
    Statistical Modelling 20(2), pp. 127-147, 2020.
  • Aleksandrov & Weiß (2020a)
    Aleksandrov, B., Weiß, C.H.: Parameter Estimation and Diagnostic Tests for INMA(1) Processes.
    TEST 29(1), pp. 196-232, 2020.
  • Puig & Weiß (2020)
    Puig, P., Weiß, C.H.: Some goodness-of-fit tests for the Poisson distribution with applications in Biodosimetry.
    Computational Statistics and Data Analysis 144, 106878, 2020.

 

2019

 

2018

  • Morais et al. (2018)
    Morais, M.C., Knoth, S., Weiß, C.H.: An ARL-unbiased thinning-based EWMA chart to monitor counts.
    Sequential Analysis 37(4), pp. 487-510, 2018.
  • Scotto et al. (2018)
    Scotto, M.G., Weiß, C.H., Möller, T.A., Gouveia, S.: The Max-INAR(1) model for count processes.
    TEST 27(4), pp. 850-870, 2018.
  • Kim et al. (2018)
    Kim, H.-Y., Weiß, C.H., Möller, T.A.: Testing for an excessive number of zeros in time series of bounded counts.
    Statistical Methods & Applications 27(4), pp. 689-714, 2018.
  • Gouveia et al. (2018)
    Gouveia, S., Möller, T.A., Weiß, C.H., Scotto, M.G.: A full ARMA model for counts with bounded support and its application to rainy-days time series.
    Stochastic Environmental Research and Risk Assessment 32(9), pp. 2495-2514, 2018.
  • Weiß et al. (2018b)
    Weiß, C.H., Steuer, D., Jentsch, C., Testik, M.C.: Guaranteed Conditional ARL Performance in the Presence of Autocorrelation.
    Computational Statistics and Data Analysis 128, pp. 367-379, 2018.
  • Weiß (2018g)
    Weiß, C.H.: Categorical Time Series Analysis.
    In Balakrishnan et al. (eds.): Wiley StatsRef: Statistics Reference Online, John Wiley & Sons Ltd, 2018.
  • Weiß (2018f)
    Weiß, C.H.: Count Time Series Analysis.
    In Balakrishnan et al. (eds.): Wiley StatsRef: Statistics Reference Online, John Wiley & Sons Ltd, 2018.
  • Weiß (2018e)
    Weiß, C.H.: Integer-valued Autoregressive Moving-Average (INARMA) Models.
    In Balakrishnan et al. (eds.): Wiley StatsRef: Statistics Reference Online, John Wiley & Sons Ltd, 2018.
  • Weiß (2018d)
    Weiß, C.H.: INGARCH and Regression Models for Count Time Series.
    In Balakrishnan et al. (eds.): Wiley StatsRef: Statistics Reference Online, John Wiley & Sons Ltd, 2018.
  • Weiß (2018c)
    Weiß, C.H.: Hidden-Markov Models for Count Time Series.
    In Balakrishnan et al. (eds.): Wiley StatsRef: Statistics Reference Online, John Wiley & Sons Ltd, 2018.
  • Weiß (2018b)
    Weiß, C.H.: Goodness-of-Fit Testing of a Count Time Series’ Marginal Distribution.
    Metrika 81(6), pp. 619-651, 2018.
  • Weiß et al. (2018a)
    Weiß, C.H., Scotto, M.G., Möller, T.A., Gouveia, S.: The max-BARMA models for Counts with Bounded Support.
    Statistics & Probability Letters 143, pp. 28-36, 2018.
  • Weiß (2018a)
    Weiß, C.H.: Control Charts for Time-Dependent Categorical Processes.
    In Knoth & Schmid (eds.): Frontiers in Statistical Quality Control 12, pp. 211-231, 2018.
  • Testik et al. (2018b)
    Testik, M.C., Weiß, C.H., Koca, Y., Testik, O.M.: Assessment of Shewhart Control Chart Limits in Phase I Implementations under Various Shift and Contamination Scenarios.
    In Knoth & Schmid (eds.): Frontiers in Statistical Quality Control 12, pp. 21-43, 2018.
  • Möller et al. (2018a)
    Möller, T.A., Weiß, C.H., Kim, H.-Y., Sirchenko, A.: Modeling Zero Inflation in Count Data Time Series with Bounded Support.
    Methodology and Computing in Applied Probability 20(2), pp. 589-609, 2018.
  • Testik et al. (2018a)
    Testik, M.C., Weiß, 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.
    Quality and Reliability Engineering International 34(1), pp. 78-92, 2018.

 

2017

  • Rakitzis et al. (2017b)
    Rakitzis, A.C., Weiß, C.H., Castagliola, P.: Control Charts for Monitoring Correlated Counts with a Finite Range.
    Applied Stochastic Models in Business and Industry 33(6), pp. 733-749, 2017.
  • Weiß (2017b)
    Weiß, C.H.: Association Rule Mining.
    In Balakrishnan et al. (eds.): Wiley StatsRef: Statistics Reference Online, John Wiley & Sons Ltd, 2017.
  • Bourguignon & Weiß (2017)
    Bourguignon, M., Weiß, C.H.: An INAR(1) process for modeling count time series with equidispersion, underdispersion and overdispersion.
    TEST 26(4), pp. 847-868, 2017.
  • Weiß (2017a)
    Weiß, C.H.: On Eigenvalues of the Transition Matrix of some Count-Data Markov Chains.
    Methodology and Computing in Applied Probability 19(3), pp. 997-1007, 2017.
  • Weiß et al. (2017)
    Weiß, C.H., Gonçalves, E., Mendes Lopes, N.: Testing the Compounding Structure of the CP-INARCH Model.
    Metrika 80(5), pp. 571-603, 2017.
  • Rakitzis et al. (2017a)
    Rakitzis, A.C., Weiß, C.H., Castagliola, P.: Control Charts for Monitoring Correlated Poisson Counts with an Excessive Number of Zeros.
    Quality and Reliability Engineering International 33(2), pp. 413-430, 2017.
  • Gouveia et al. (2017)
    Gouveia, S., Scotto, M.G., Weiß, C.H., Ferreira, P.J.S.G.: Binary autoregressive geometric modelling in a DNA context.
    Journal of the Royal Statistical Society (Series C) 66(2), pp. 253-271, 2017.
  • Alwan & Weiß (2017)
    Alwan, L.C., Weiß, C.H.: INAR Implementation of Newsvendor Model for Serially Dependent Demand Counts.
    International Journal of Production Research 55(4), pp. 1085-1099, 2017.

2016

  • Ristić et al. (2016)
    Ristić, M.M., Weiß, C.H., Janjić, A.D.: A binomial integer-valued ARCH model.
    International Journal of Biostatistics 12(2), 20150051, 2016.
  • Möller et al. (2016)
    Möller, T.A., Silva, M.E., Weiß, C.H., Scotto, M.G., Pereira, I.: Self-Exciting Threshold Binomial Autoregressive Processes.
    Advances in Statistical Analysis 100(4), pp. 369-400, 2016.
  • Schweer & Weiß (2016)
    Schweer, S., Weiß, C.H.: Testing for Poisson Arrivals in INAR(1) Processes.
    TEST 25(3), pp. 503-524, 2016.
  • Dasdemir et al. (2016)
    Dasdemir, E., Weiß, C.H., Testik, M.C., Knoth, S.: Evaluation of Phase I analysis scenarios on Phase II performance of control charts for autocorrelated observations.
    Quality Engineering 28(3), pp. 293-304, 2016.
  • Weiß & Schweer (2016)
    Weiß, C.H., Schweer, S.: Bias Corrections for Moment Estimators in Poisson INAR(1) and INARCH(1) Processes.
    Statistics and Probability Letters 112, pp. 124-130, 2016.
  • Möller (2016)
    Möller, T.A.: Self-Exciting Threshold Models for Time Series of Counts with a Finite Range.
    Stochastic Models 32(1), pp. 77-98, 2016.

2015

  • Scotto et al. (2015)
    Scotto, M.G., Weiß, C.H., Gouveia, S.: Thinning-based models in the analysis of integer-valued time series: a review.
    Statistical Modelling 15(6), pp. 590-618, 2015.
  • Freyn & Weiß (2015)
    Freyn, W., Weiß, C.H.: Neue Maßnahmen für eine verbesserte Schulung und Betreuung von Übungsleitern.
    In Hoppenbrock et al. ( Hrsg.), Lehren und Lernen von Mathematik in der Studieneingangsphase – Herausforderungen und Lösungsansätze, pp. 213-227, 2015.
  • Weiß (2015c)
    Weiß, C.H.: SPC Methods for Time-Dependent Processes of Counts – A Literature Review.
    Cogent Mathematics 2(1): 1111116, 2015.
  • Weiß (2015b)
    Weiß, C.H.: A Poisson INAR(1) Model with Serially Dependent Innovations.
    Metrika 78(7), pp. 829-851, 2015.
  • Weiß & Schweer (2015)
    Weiß, C.H., Schweer, S.: Detecting Overdispersion in INARCH(1) Processes.
    Statistica Neerlandica 69(3), pp. 281-297, 2015.
  • Weiß (2015a)
    Weiß, C.H.: Sampling in Data Mining.
    In Balakrishnan et al. (Eds.): Wiley StatsRef: Statistics Reference Online, John Wiley & Sons Ltd, 2015.
  • Kim & Weiß (2015)
    Kim, H.-Y., Weiß, C.H.: Goodness-of-Fit Tests for Binomial AR(1) Processes.
    Statistics: A Journal of Theoretical and Applied Statistics 49(2), pp. 291-315, 2015.
  • Weiß & Testik (2015b)
    Weiß, C.H., Testik, M.C.: On the Phase I Analysis for Monitoring Time-Dependent Count Processes.
    IIE Transactions 47(3), pp. 294-306, 2015.
  • Weiß & Testik (2015a)
    Weiß, C.H., Testik, M.C.: Residuals-based CUSUM Charts for Poisson INAR(1) Processes.
    Journal of Quality Technology 47(1), pp. 30-42, 2015.
  • Weiß & Puig (2015)
    Weiß, C.H., Puig, P.: The Marginal Distribution of Compound Poisson INAR(1) Processes.
    Steland et al. (eds.): Stochastic Models, Statistics and Their Applications, Springer Proceedings in Mathematics & Statistics 122, Springer-Verlag, pp. 351-359, 2015.
  • Möller & Weiß (2015)
    Möller, T.A., Weiß, C.H.: Threshold models for integer-valued time series with infinite and finite range.
    Steland et al. (eds.): Stochastic Models, Statistics and Their Applications, Springer Proceedings in Mathematics & Statistics 122, Springer-Verlag, pp. 327-334, 2015.

2014

2013

2012

2011

  • Weiß (2011f)
    Weiß, C.H.: Simultaneous Confidence Regions for the Parameters of a Poisson INAR(1) Model.
    Statistical Methodology 8(6), pp. 517-527, 2011.
  • Weiß & Testik (2011)
    Weiß, C.H., Testik, M.C.: The Poisson INAR(1) CUSUM Chart under Overdispersion and Estimation Error.
    IIE Transactions 43(11), pp. 805-818, 2011.
  • Weiß (2011e)
    Weiß, C.H.: Generalized Choice Models for Categorical Time Series.
    Journal of Statistical Planning and Inference 141(8), pp. 2849-2862, 2011.
  • Weiß (2011d)
    Weiß, C.H.: Empirical Measures of Signed Serial Dependence in Categorical Time Series.
    Journal of Statistical Computation and Simulation 81(4), pp. 411-429, 2011.
  • Weiß (2011c)
    Weiß, C.H.: The Markov Chain Approach for Performance Evaluation of Control Charts – A Tutorial.
    Chapter 11 in Samuel P. Werther (Ed.): Process Control: Problems, Techniques and Applications, ISBN 978-1-61209-567-7, Nova Science Publishers, Inc., pp. 205-228, 2011.
  • Weiß (2011b)
    Weiß, C.H.: Rule Generation for Categorical Time Series with Markov Assumptions.
    Statistics and Computing 21(1), pp. 1-16, 2011.
  • Weiß (2011a)
    Weiß, C.H.: Detecting Mean Increases in Poisson INAR(1) Processes with EWMA Control Charts.
    Journal of Applied Statistics 38(2), pp. 383-398, 2011.

2010

2009

2008

2007

 

 

2024

  • August 2024
    Testing for Serial Dependence by Using Ordinal Patterns.
    Invited talk, Bernoulli-ims 11th World Congress in Probability and Statistics, Bochum, 12. – 16. August, 2024. (Folien_08_24.pdf)
  • May 2024
    Anomaly Detection in Ordinal Quality-Related Processes by Control Charts.
    ENBIS Spring Meeting 2024, Dortmund, 15. – 16. May, 2024. (Folien_05_24.pdf)
  • May 2024
    Non-parametric Control Charts for Monitoring Serial Dependence based on Ordinal Patterns.
    Invited talk (14.05.2024), Oberseminar Stochastik, Universität Siegen.
  • March 2024
    Using Spatial Ordinal Patterns for Non-parametric Testing of Spatial Dependence.
    Invited talk (14.03.2024), 15th Workshop on Stochastic Models and Their Applications, Delft, 13. – 15. March, 2024. (Folien_03_24.pdf)
  • January 2024
    Testing for Dependence by Using Ordinal Patterns: an Introduction.
    Invited talk (24.01.2024), Statistisches Kolloquium, TU Dortmund.

 

2023

  • September 2023
    Multiplicative Error Models for Count Time Series.
    Statistische Woche 2023, Dortmund, 11. – 13. September, 2023. (Folien_09_23.pdf)
  • Juli 2023
    Ordinal Compositional Data and Time Series.
    37th International Workshop on Statistical Modelling (IWSM 2023), Dortmund, 17. – 21. Juli, 2023. (Folien_07_23.pdf)
  • May 2023
    Stein EWMA Control Charts for Count Processes.
    Invited talk, Conference of the Greek Statistical Institute (GSI), 25. – 28. May, 2023. (Folien_05_23.pdf)
  • March 2023
    Optimal Stein-type Goodness-of-Fit Tests for Count Data.
    German Probability and Statistics Days 2023 (Stochastik-Tage 2023), Essen, 7. – 10. March, 2023. (Folien_03_23.pdf)

 

2022

  • December 2022
    An Introduction to Categorical Time Series Analysis.
    Invited talk (21.12.2022), Colloquium, Institute for Mathematics and Applied Informatics, University of Hildesheim.
  • September 2022
    Non-parametric Monitoring of Serial Dependence based on Ordinal Patterns.
    Statistische Woche 2022, Münster, 20. – 23. September, 2022. (Folien_09_22.pdf)
  • July 2022
    Approximately Linear INGARCH Models for Spatio-Temporal Counts.
    Invited talk (06.07.2022), 3rd LmB Conference on Multivariate Statistical Models: Count and Semi-Continuous, Université de Franche-Comté in Besançon, France, 06. Juli – 08. Juli, 2022. (Folien_07_22.pdf)
  • March 2022
    Approximately Linear INGARCH Models for Spatio-Temporal Counts.
    DAGStat-Tagung 2022: Sechste gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universität Hamburg, 29. March – 1. April, 2022. (Folien_03_22_2.pdf)
  • March 2022
    An Introduction to Categorical Time Series Analysis.
    Invited talk (18.03.2022), Statistics seminar, Department of Mathematics and Statistics, University of Jyväskylä.
  • March 2022
    Measuring Dispersion and Serial Dependence in Ordinal Time Series based on the Cumulative Paired ϕ-Entropy.
    Invited talk, Workshop on “Ordinal methods: Concepts, applications, new developments and challenges” (ORPATT22), MPI-PKS in Dresden, 28. February – 4. March, 2022. (Folien_03_22_1.pdf)

 

2021

  • September 2021
    Some goodness-of-fit tests for the Poisson distribution with applications in Biodosimetry.
    German Probability and Statistics Days 2021 (Stochastik-Tage 2021), Mannheim, 27. September – 1. Oktober, 2021. (Folien_09_21_4.pdf, video)
  • September 2021
    Soft-clipping INGARCH Models for Time Series of Bounded Counts.
    Statistische Woche 2021, 14. – 17. September, 2021. (Folien_09_21_3.pdf)
  • September 2021
    Analyzing categorical time series in the presence of missing observations.
    21th Annual Conference of ENBIS (Online Conference), 13. – 15. September, 2021. (Folien_09_21_2.pdf)
  • September 2021
    On Approaches for Monitoring Categorical Event Series.
    Keynote talk, 22nd European Young Statisticians Meeting (EYSM 2021), Panteion University Athens, 6. – 10. September, 2021. (Folien_09_21_1.pdf)
  • July 2021
    On PMF-Forecasting for Count Processes.
    Plenary talk (video), 7th International conference on Time Series and Forecasting (ITISE 2021), Granada, 19. – 21. July, 2021. (Folien_07_21.pdf)
  • May 2021
    Efficient Accounting for Estimation Uncertainty in Coherent Forecasting of Count Processes.
    ENBIS 2021 Spring Meeting, Newcastle, 17. – 18. May, 2021. (Folien_05_21.pdf)

 

2020

Because of the Corona crisis, all talks yet planned for 2020 had to be cancelled.

     

    2019

    • September 2019
      Time Series Modeling for Categorical Data.
      Invited lecture, 2nd Dortmund-Bielefeld Summer School on Modern Topics in Time Series Analysis, University of Bielefeld, 10. September, 2019. (Details)
    • September 2019
      Evaluating Approximate Point Forecasting of Count Processes.
      19th Annual Conference of ENBIS, Budapest, 2. – 4. September, 2019. Folien_09_19.pdf)
    • Juni 2019
      Discrete-Valued Time Series.
      Invited lecture, XIII Summer School in Statistics UPC-UB 2019 at the Universitat Politècnica de Catalunya in Barcelona, 25.-28. Juni, 2019. (Details)
    • März 2019
      Distance-based Analysis of Ordinal Time Series.
      DAGStat-Tagung 2019: Statistik unter einem Dach, Fünfte gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, LMU München, 19. – 22. März, 2019. (Folien_03_19_2.pdf)
    • März 2019
      Generalized Discrete ARMA Models.
      Invited talk (07.03.2019), 14th Workshop on Stochastic Models and Their Applications, Dresden, 6. – 8. März, 2019. (Folien_03_19_1.pdf)

     

    2018

    • November 2018
      SPC methods for time-dependent processes of counts.
      Invited talk (29.11.2018), Forschungsseminar des Lehrstuhls für Quantitative Methoden, insb. Statistik, Europa-Universität Viadrina Frankfurt/Oder.
    • November 2018
      An Introduction to Count Time Series Analysis.
      Invited talk (27.11.2018), Kolloquium über Mathematische Statistik und Stochastische Prozesse, Universität Hamburg.
    • November 2018
      Distance-based Analysis of Ordinal Data and Ordinal Time Series.
      Invited talk (21.11.2018), Statistisches Seminar des Lehrstuhls für Statistik und Ökonometrie, FAU Nürnberg.
    • September 2018
      A Short Course in Categorical Time Series Analysis.
      Invited lecture, Department of Quantitative and Computing Methods, Universidad Politécnica de Cartagena, 11.-12. September, 2018. (Details)
    • September 2018
      Using Risk Metrics for Performance Evaluation of Control Charts.
      18th Annual Conference of ENBIS, Nancy, 3. – 5. September, 2018. (Folien_09_18.pdf)
    • Juli 2018
      Model diagnostics for Poisson INARMA processes using bivariate dispersion indexes.
      Invited talk (04.07.2018), The LmB Conferences on Multivariate Count Analysis, Université de Franche-Comté in Besançon, France, 04. Juli – 06. Juli, 2018. (Folien_07_18.pdf)
    • Juni 2018
      An Introduction to Count Time Series Analysis.
      Invited talk (21.06.2018), Oberseminar des Instituts für Mathematische Stochastik, TU Braunschweig.
    • April 2018
      An Introduction to Count Time Series Analysis with Applications in Economics.
      Invited talk (25.04.2018), Ökonomisches Forschungsseminar, WWU Münster.
    • Februar 2018
      On Eigenvalues of the Transition Matrix of some Count-Data Markov Chains.
      13th German Probability and Statistics Days 2018 (Stochastik-Tage 2018), Freiburg, 27. Februar – 02. März, 2018. (Folien_02_18.pdf)

     

    2017

    • Dezember 2017
      Analysis and Modeling of Categorical Time Series: Difficulties and Possible Solutions.
      Invited talk (07.12.2017), Kolloquium, Institut für Mathematik, Universität zu Lübeck.
    • September 2017
      Guaranteed Conditional ARL Performance in the Presence of Autocorrelation.
      Statistische Woche, Jahrestagung 2017, Rostock, 19. – 22. September, 2017. (Folien_09_17_2.pdf)
    • September 2017
      Goodness-of-Fit Testing for Count Time Series.
      Invited talk (10.09.2017), 3rd Workshop on Goodness-of-fit and Change-Point Problems, Bad Herrenalb, 8. – 10. Septempter, 2017. (Folien_09_17_1.pdf)
    • Februar 2017
      Testing the Compounding Structure of the CP-INARCH Model.
      13th Workshop on Stochastic Models and Their Applications, Berlin, 20. – 24. Februar, 2017. (Folien_02_17.pdf)

    2016

    • November 2016
      Analyse und Modellierung von Zähldatenzeitreihen mit Anwendungen im Verkehrswesen.
      Invited talk (29.11.2016), Brown Bag Seminar, TU Dresden.
    • November 2016
      Modeling and Analysis of Count Data Time Series: An Introduction.
      Invited talk (09.11.2016), Uppsala Mathematics Colloquium, Department of Mathematics, Uppsala University.
    • September 2016
      Diagnostic Tests for Binomial AR(1) Processes.
      Statistische Woche, Jahrestagung 2016, Augsburg, 13. – 16. September, 2016. (Folien_09_16.pdf)
    • August 2016
      Control Charts for Time-Dependent Categorical Processes.
      12th International Workshop on Intelligent Statistical Quality Control (ISQC 2016), Hamburg, August 16. – 19., 2016. (Folien_08_16.pdf)
    • Mai 2016
      On Eigenvalues of the Transition Matrix of some Count Data Markov Chains.
      Invited talk (11.05.2016), CEMAT’s Open Seminar and Probability and Statistics Seminar, Department of Mathematics of Instituto Superior Técnico, Lisboa.
    • März 2016
      SPC Methods for Time-Dependent Processes of Counts.
      Poster-Präsentation, DAGStat-Tagung 2016: Statistik unter einem Dach, Vierte gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universität Göttingen, 15. – 18. März, 2016. (Poster_03_16.pdf)
    • März 2016
      Introduction to Integer-Valued Time Series.
      Invited lecture, Tutorial, DAGStat-Tagung 2016: Statistik unter einem Dach, Vierte gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universität Göttingen, 14. März, 2016. (Details)
    • März 2016
      Time Reversibility of INAR(1) Processes and Testing for Poisson Innovations.
      12th German Probability and Statistics Days 2016 (Stochastik-Tage 2016), Bochum, 01. – 04. März, 2016. (Folien_03_16.pdf)

    2015

    • Oktober 2015
      An Introduction to Categorical Time Series Analysis.
      Invited talk, Research Seminar in Mathematical Econometrics, Stochastics and Finance (15.10.2015), Lehrstuhl für Statistik, Universität Mannheim.
    • September 2015
      Binomial Autoregressive Process with Density Dependent Thinning.
      2015 NBER/NSF Time Series Conference, Wien, 25. – 26. September, 2015. (Folien_09_15_3.pdf)
    • September 2015
      Analysis and Modelling of Categorical Time Series.
      Poster-Präsentation, Statistische Woche, Jahrestagung 2015, Hamburg, 15. – 18. September, 2015. (Poster_09_15.pdf)
    • September 2015
      Bias Corrections for Moment Estimators in Poisson INAR(1) and INARCH(1) Processes.
      Statistische Woche, Jahrestagung 2015, Hamburg, 15. – 18. September, 2015. (Folien_09_15_2.pdf)
    • September 2015
      Newsvendor Model in Presence of Correlated Discrete Demand.
      15th Annual Conference of ENBIS, Prag, 7. – 9. September, 2015. (Folien_09_15_1.pdf)
    • Februar 2015
      The Marginal Distribution of Compound Poisson INAR(1) Processes.
      12th Workshop on Stochastic Models and Their Applications, Wroclaw, 17. – 20. Februar, 2015. (Folien_02_15.pdf)
    • Februar 2015
      Modeling and Analysis of Count Data Time Series: Recent Research Activities.
      Invited talk (03.02.2015), Centre for Mathematics, University of Coimbra.

    2014

    • September 2014
      Integer-Valued Autoregressive Models for Counts Showing Underdispersion.
      14th Annual Conference of ENBIS, Linz, 22. – 24. September, 2014. (Folien_09_14_2.pdf)
    • September 2014
      Binomial Models for Count Data Time Series with a Finite Range.
      Poster-Präsentation, Statistische Woche, Jahrestagung 2014, Hannover, 16. – 19. September, 2014. (Poster_09_14.pdf)
    • September 2014
      Serial Dependence in Categorical Time Series.
      Statistische Woche, Jahrestagung 2014, Hannover, 16. – 19. September, 2014. (Folien_09_14_1.pdf)
    • Juli 2014
      Zur Eröffnung der Ausstellung “Fraktale Stadtansichten” von Hiltrud Heinrich.
      Laudatio (06.07.2014), Vernissage in der Galerie “ART Bessungen”, Darmstadt.
    • Juli 2014
      Diagnosing Overdispersion in Count Data Time Series.
      Invited talk (02.07.2014), Workshop “Count Data Modeling and Analysis”, LMB trimesters, Université de Franche-Comté in Besançon, France, 30. Juni – 04. Juli, 2014. (Folien_07_14.pdf)
    • Juni 2014
      An Introduction to Integer-Valued Time Series Models.
      Invited lecture (30.06.2014), Mini-course “Integer-Valued Time Series Models”, LMB trimesters, Université de Franche-Comté in Besançon, France, 30. Juni – 04. Juli, 2014. (Details)
    • März 2014
      Bivariate Binomial Autoregressive Models.
      11th German Probability and Statistics Days 2014 (Stochastik-Tage 2014), Ulm, 04. – 07. März, 2014. (Folien_03_14.pdf)

    2013

    • September 2013
      Phase-I Analysis of Time-Dependent Counts with Missing Observations.
      13th Annual Conference of ENBIS, Ankara, 16. – 18. September, 2013. (Folien_09_13.pdf)
    • Mai 2013
      Mathematikausbildung für INT-Studierende an der TU Darmstadt – Erfahrungen und neue Konzepte.
      Keynote Lecture (28.05.2013), Workshop “Eine Woche Zeit – Wege aus der MINT-Schwäche: Neue inhaltliche und didaktische Konzepte für die universitäre Mathematik-Ausbildung”, Gut Siggen, 27. Mai – 1. Juni, 2013.
    • März 2013
      Residuals-based CUSUM Charts for Poisson INAR(1) Processes.
      DAGStat-Tagung 2013: Statistik unter einem Dach, Dritte gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universität Freiburg, 19. – 22. März, 2013. (Folien_03_13_2.pdf)
    • März 2013
      Diagnosing and Modelling Extra-Binomial Variation for Time-Dependent Counts.
      DAGStat-Tagung 2013: Statistik unter einem Dach, Dritte gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universität Freiburg, 19. – 22. März, 2013. (Folien_03_13_1.pdf)
    • Februar 2013
      Compound Poisson INAR(1) Processes: Stochastic Properties and Testing for Overdispersion.
      11th Workshop on Stochastic Models and Their Applications, Hamburg, 20. – 22. Februar, 2013. (Folien_02_13.pdf)

    2012

    • September 2012
      Modeling and Analysis of Count Data Time Series: Recent Research Activities.
      Invited talk (25.09.2012), Mathematics Department, University of Aveiro.
    • September 2012
      Chain Binomial Models and Binomial Autoregressive Processes.
      Statistische Woche, Jahrestagung 2012, Wien, 18. – 21. September, 2012. (Folien_09_12_2.pdf)
    • September 2012
      Detection of Abrupt Changes in Count Data Time Series: Cumulative Sum Derivations for INARCH(1) Models
      Twelvth Annual Conference of ENBIS, Ljubljana, 10. – 12. September, 2012. (Folien_09_12_1.pdf)

    2011

    • November 2011
      Analyse und Modellierung von Zähldatenzeitreihen.
      Invited talk, Forschungsseminar des Lehrstuhls für Statistik (10.11.2011), Universität Augsburg.
    • Oktober 2011
      Ein erweitertes Poisson INAR(1)-Modell
      Invited talk, Workshop des Zentrums für Statistik der TU Darmstadt, Grasellenbach, 05. – 06. Oktober, 2011. (Folien_10_11.pdf)
    • September 2011
      Empirical Measures of Signed Serial Dependence in Categorical Time Series.
      Statistische Woche, Jahrestagung 2011, Leipzig, 20. – 23. September, 2011. (Folien_09_11_2.pdf)
    • September 2011
      Categorical Time Series: Analysis, Modelling, Monitoring?
      Invited talk (Young Statistician’s Award), Eleventh Annual Conference of ENBIS, Coimbra, 05. – 07. September, 2011. (Folien_09_11_1.pdf)
    • März 2011
      Continuously Monitoring Categorical Processes.
      10th Workshop on Stochastic Models and Their Applications, Wismar, 01. – 04. März, 2011. (Folien_03_11.pdf)

    2010

    • September 2010
      Process Capability Analysis for Serially Dependent Processes of Poisson Counts.
      Invited talk, Tenth Annual Conference of ENBIS, Antwerpen, 13. – 15. September, 2010. (Folien_09_10.pdf)
    • Juni 2010
      AR(1)-Modelle für Zähldatenzeitreihen.
      Invited talk, Kolloquium der Fächergruppe Mathematik und Statistik (21.06.2010), Helmut-Schmidt-Universität Hamburg.
    • März 2010
      Detecting Mean Increases in Poisson INAR(1) Processes with EWMA Control Charts.
      DAGStat-Tagung 2010: Statistik unter einem Dach, Zweite gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, TU Dortmund, 23. – 26. März, 2010. (Folien_03_10.pdf)

    2009

    • Oktober 2009
      The INARCH(1) Model for Overdispersed Time Series of Counts.
      Statistische Woche, Jahrestagung 2009, Wuppertal, 5. – 8. Oktober, 2009. (Folien_10_09.pdf)
    • September 2009
      EWMA Control Charts for Monitoring Binary Processes with Applications to Medical Diagnosis Data.
      Ninth Annual Conference of ENBIS, Göteburg, 21. – 23. September, 2009. (Folien_09_09.pdf)
    • Juni 2009
      Statistische Kontrolle von Zähldatenprozessen mit Überdispersion.
      Pfingsttagung der Deutschen Statistischen Gesellschaft, Merseburg, 04. – 05. Juni, 2009. (Folien_06_09.pdf)
    • April 2009
      Modellierung und Kontrolle von Zähldatenprozessen.
      Invited talk, Dresdner Kolloquium zur Stochastik (14.04.2009), Institut für Mathematische Stochastik, Technische Universität Dresden.
    • März 2009
      CUSUM Monitoring of First-Order Integer-Valued Autoregressive Processes of Poisson Counts.
      9th Workshop on Stochastic Models and Their Applications, Aachen, 03. – 06. März, 2009. (Folien_03_09.pdf)

    2008

    • Dezember 2008
      Modeling and Control of Count Data Processes.
      Invited talk, Forschungsseminar (02.12.2008), Lehrstuhl für Quantitative Methoden, insb. Statistik, Europa-Universität Viadrina Frankfurt (Oder).
    • November 2008
      Modeling and Control of Count Data Processes.
      Invited talk, Oberseminar Stochastik (20.11.2008), Fakultät für Mathematik, Otto-von-Guericke-Universität Magdeburg.
    • September 2008
      Group Inspection of Dependent Binary Processes.
      Eighth Annual Meeting of ENBIS, Athen, 22. – 24. September, 2008. (Folien_09_08_2.pdf)
    • September 2008
      Controlling Jumps in Poisson INAR(1) Processes.
      Statistische Woche, Jahrestagung 2008, Köln, 15. – 18. September, 2008. (Folien_09_08_1.pdf)
    • August 2008
      Commercial meets Open Source – Tuning STATISTICA with R.
      useR! – The R User Conference 2008, Dortmund, 12. – 14. August, 2008. (Folien_08_08.pdf)
    • Mai 2008
      EWMA-Kontrollkarten für korrelierte Zähldatenprozesse mit Poisson-Randverteilung.
      Pfingsttagung der Deutschen Statistischen Gesellschaft, Berlin, 14. – 16. Mai, 2008. (Folien_05_08.pdf)
    • März 2008
      A New Class of Autoregressive Models for Time Series of Binomial Counts.
      8th German Open Conference on Probability and Statistics (GOCPS 2008, “Aachener Stochastik-Tage”), Aachen, 04. – 07. März, 2008. (Folien_03_08.pdf)

    2007

    • September 2007
      Controlling Correlated Processes with Binomial Marginals.
      Seventh Annual Meeting of ENBIS, Dortmund, 24. – 26. September, 2007. (Folien_09_07.pdf)
    • April 2007
      Zufall als Werkzeug – Monte-Carlo-Methoden in der Kunst.
      Ausgerechnet … Mathematik und Konkrete Kunst, Nacht der Mathematik, Kulturspeicher Würzburg, 26. April, 2007.
    • März 2007
      Visual Analysis of Categorical Time Series.
      DAGStat-Tagung 2007: Statistik unter einem Dach, Erste gemeinsame Tagung der Deutschen Arbeitsgemeinschaft Statistik, Universität Bielefeld, 27. – 30. März, 2007. (Folien_03_07.pdf)

    2006

    • September 2006
      Controlling Correlated Processes of Poisson Counts.
      Sixth Annual Meeting of ENBIS, Breslau, Polen, 18. – 20. September, 2006. (Folien_09_06.pdf)
    • Juni 2006
      Measuring Serial Dependence in Categorical Time Series.
      Pfingsttagung der Deutschen Statistischen Gesellschaft, Helmut-Schmidt-Universität, Hamburg, 07. – 09. Juni, 2006. (Folien_06_06.pdf)

    2005

    • September 2005
      Discover Patterns in Categorical Time Series using IFS.
      Fifth Annual Meeting of ENBIS, Newcastle, UK, 14. – 16. September, 2005. (Folien_09_05.pdf)
    • März 2005
      Sequential Pattern Analysis und Markov-Modelle.
      7. Workshop Stochastische Modelle und ihre Anwendungen, Würzburg, Schönstattzentrum Marienhöhe, 7. – 10. März 2005. (Folien_03_05.pdf)

     

    HSU

    Letzte Änderung: 4. April 2024