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• [6]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2984297

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

  PUB | Download (ext.)
   
• [5]
  

  2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2957037

  L. Oelschläger and T. Adam, “Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov models”, Statistical Modelling, vol. 23, 2021, pp. 107-126.

  PUB | DOI | WoS
   
• [4]
  

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

  L. Oelschläger and D. Bauer, “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

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

  PUB
   
• [2]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982766

  T. Adam and L. Oelschläger, “Hidden Markov models for multi-scale time series: an application to stock market data”, Proceedings of the 35th International Workshop on Statistical Modelling. Part I, I. Irigoien, et al., eds., Bilbao: Universidad del País Vasco, 2020, pp.2-7.

  PUB
   
• [1]
  

  2020 | Konferenzbeitrag | PUB-ID: 2951071

  L. Oelschläger and D. Bauer, “Bayes Estimation of Latent Class Mixed Multinomial Probit Models”, Presented at the TRB Annual Meeting 2021, 2020.

  PUB