Lennart Oelschläger
lennart.oelschlaeger@uni-bielefeld.dehttps://orcid.org/0000-0001-5421-9313
PEVZ-ID
6 Publikationen
-
2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2984297Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-takingPUB | Download (ext.)
Oelschläger, Lennart, Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking. Proceedings of the 37th International Workshop on Statistical Modelling (). , 2023 -
2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2957037Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov modelsPUB | DOI | WoS
Oelschläger, Lennart, Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov models. Statistical Modelling 23 (2). , 2021 -
2021 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2951073Bayes Estimation of Latent Class Mixed Multinomial Probit ModelsPUB | PDF
Oelschläger, Lennart, Bayes Estimation of Latent Class Mixed Multinomial Probit Models. (). , 2021 -
2021 | Wissenschaftliche Software | PUB-ID: 2982764fHMM: fitting hidden Markov models to financial data (R package)PUB
Oelschläger, Lennart, fHMM: fitting hidden Markov models to financial data (R package). (). , 2021 -
2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982766Hidden Markov models for multi-scale time series: an application to stock market dataPUB
Adam, Timo, 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 (). Bilbao, 2020 -
2020 | Konferenzbeitrag | PUB-ID: 2951071Bayes Estimation of Latent Class Mixed Multinomial Probit ModelsPUB
Oelschläger, Lennart, Bayes Estimation of Latent Class Mixed Multinomial Probit Models. (). , 2020