Research areas / ÖSTAT - Subject areas
- Data science
- Software development
- Time series analysis
I am interested in Bayesian modelling of time series data, mainly through Markov chain Monte Carlo (MCMC) methods. This usually requires high performance computing infrastructures. My current research focus is the efficient Bayesian estimation of univariate and multivariate stochastic volatility (SV) and vector autoregressive (VAR) models as well as statistical modeling of economic data. I am founder of and active contributor to the open-source R packages stochvol and factorstochvol.
2014: Dr.techn. (JKU Linz, WU Wien: Applied Mathematics)
2011: Mag.rer.nat. (University of Vienna: Physical Education)
2009: Mag.rer.nat. (TU Wien, University of Vienna: Computer Science)
2009: Mag.rer.soc.oec. (TU Wien, University of Vienna: Informatics Management)
2006: Dipl.-Ing. (TU Wien, ETH Zurich: Applied Mathematics)
Darjus Hosszejni, Gregor Kastner: Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol. Journal of Statistical Software, 100, 2021, S. 1 - 34.
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