Lehrveranstaltungen
- Statistik II – Übung (FT 2018)
- Mathematik für Wirtschaftswissenschaftler – Übung (HT 2015, 2017)
- Fortgeschrittene Mathematik für Ökonomen – Vorlesung (WT 2017)
- Mathematik für Wirtschaftswissenschaftler – Vorlesung (HT 2016)
- Fortgeschrittene Mathematik für Ökonomen – Übung (WT 2015, 2016)
- Grundlagen der Zeitreihenanalyse – Übung (FT 2015)
Publikationen
- Kim, H.-Y., Weiß, C.H., Möller, T.A. [2020] Models for Autoregressive Processes of Bounded Counts: How Different Are They?
Computational Statistics 35(4), pp. 1715-1736. - Möller, T.A., Weiß, C.H. [2020] Generalized Discrete ARMA Models.
Applied Stochastic Models in Business and Industry 36(4), pp. 641-659. - Möller, T.A., Weiß, C.H., Kim, H.-Y.: Modeling Counts with State-Dependent Zero Inflation.
Statistical Modelling 20(2), pp. 127-147, 2020. - Möller, T.M. [2019] An Application of the Max-INAR(1) Model to Counts of Cinema Visitors.
In Steland et al. (eds.): Stochastic Models, Statistics and Their Applications, Springer Proceedings in Mathematics & Statistics, Vol. 294, Springer International Publishing, pp. 315-322. - Weiß, C.H., Scotto, M.G., Möller, T.A., Gouveia, S. [2018] ‚The max-BARMA models for counts with bounded support‘, Statistics & Probability Letters 143, pp. 28-36.
- Gouveia, S., Möller, T.A., Weiß, C.H., Scotto, M.G. [2018] ‚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.
- Kim, H.-Y., Weiß, C.H., Möller, T.A. [2018] ‚Testing for an excessive number of zeros in time series of bounded counts‘, Statistical Methods and Applications 27(4), pp. 689-714.
- Möller, T.A., Weiß, C.H., Kim, H.-Y., Sirchenko, A. [2018] ‚Modeling Zero Inflation in Count Data Time Series with Bounded Support‘, Methodology and Computing in Applied Probability 20(2), pp. 589-609.
- Scotto, M.G., Weiß, C.H., Möller, T.A., Gouveia, S. [2018] ‚The Max-INAR(1) model for count processes‘, TEST 27(4), pp. 850-870.
- Möller, T.A., Silva, M.E., Weiß, C.H., Scotto, M.G., Pereira, I. [2016] ‚Self-Exciting Threshold Binomial Autoregressive Processes‘. AStA Advances in Statistical Analysis 100(4), pp. 369-400.
- Möller, T.A. [2016] ‚Self-Exciting Threshold Models for Time Series of Counts with a Finite Range‘, Stochastic Models 32(1), pp. 77-98.
- Möller, T. A. and Weiß, C. H. [2015] ‚Threshold models for integer-valued time series with
infinite or finite range‘ in A. Steland, E. Rafajlowicz and K. Szajowski, eds, ‚Stochastic
Models, Statistics and Their Applications‘, Vol. 122 of Springer Proceedings in Mathematics
& Statistics, Springer International Publishing, pp. 327-334.
Vorträge
- A Full ARMA Model for Counts with Bounded Support and its Application to Rainy-Days Time Series ( XXIII Congresso
da Sociedade Portuguesa de Estatística, Lissabon – Oktober 2017) - A Full ARMA Model for Counts with Bounded Support (Workshop SMSA 2017, Berlin – Februar 2017)
- Zero-Inflation Models for Count Data Time Series with a Finite Range (DAGStat, Göttingen – März 2016)
- On Some Models for Count Data Time Series with a Finite Range (Invited Talk, Aveiro – November 2015)
- Self-Exciting Threshold Binomial INARCH(1) Process (Statistische Woche, HSU Hamburg – September 2015)
- Self-Exciting Threshold Models for Integer-Valued Time Series with Inifinite or Finite Range (Workshop SMSA, Breslau – Februar 2015)
- Self-Exciting Threshold Binomial AR(1) Model (Nachwuchsworkshop der DStatG, Hannover – September 2014)
Letzte Änderung: 18. Februar 2026