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• [6]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2984297

  Oelschläger, L., Bauer, D.: Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking. In: TU Dortmund University (ed.) Proceedings of the 37th International Workshop on Statistical Modelling. p. 549-553. (2023).

  PUB | Download (ext.)
   
• [5]
  

  2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2957037

  Oelschläger, L., Adam, T.: Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov models. Statistical Modelling. 23, 107-126 (2021).

  PUB | DOI | WoS
   
• [4]
  

  2021 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2951073

  Oelschläger, L., Bauer, D.: Bayes Estimation of Latent Class Mixed Multinomial Probit Models. Presented at the TRB Annual Meeting 2021, Online (2021).

  PUB | PDF
   
• [3]
  

  2021 | Wissenschaftliche Software | PUB-ID: 2982764

  Oelschläger, L., Adam, T., Michels, R.: fHMM: fitting hidden Markov models to financial data (R package). CRAN (2021).

  PUB
   
• [2]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982766

  Adam, T., Oelschläger, L.: Hidden Markov models for multi-scale time series: an application to stock market data. In: Irigoien, I., Lee, D.-J., Martínez-Minaya, J., and Rodríguez-Álvarez, M.X. (eds.) Proceedings of the 35th International Workshop on Statistical Modelling. Part I. p. 2-7. Universidad del País Vasco, Bilbao (2020).

  PUB
   
• [1]
  

  2020 | Konferenzbeitrag | PUB-ID: 2951071

  Oelschläger, L., Bauer, D.: Bayes Estimation of Latent Class Mixed Multinomial Probit Models. Presented at the TRB Annual Meeting 2021 (2020).

  PUB