Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

Docendo discimus

^Seneca

Research interests

• Reduction of dimensionality
• Quantiles and Expectiles
• Regression shrinkage methods

Education

• Ph.D. in Statistics, Humboldt-Universität zu Berlin, DE
• Master of Probability, Math.Statistics and Econometrics, Charles University in Prague, CZ
• Bachelor of General Mathematics, Charles University in Prague, CZ

Teaching

• Privatissimum Statistik Seminar (SoSe18) (WiSe18/19)
• Economic Risk Seminar (SoSe18) (WiSe18/19)
• Mathematical Statistics Seminar (SoSe18) (WiSe18/a9)
• Statistical Programming Languages (SoSe18)
  This class is supported by DataCamp that provides free access to premium classes
• Multivariate Statistical Analysis I (WiSe16/17)
• Multivariate Statistical Analysis II (SoSe17) (SoSe18)
• Numerical Introductory Course (Seminar WiSe15/16) (Seminar WiSe18/19)
• Statistik II.(Tutorial WiSe14/15)
  Material: SET1, SET2, SET3, SET4, SET5, SET6, SET7, (SET7-excel sheet)
• Statistik I. (Tutorial SoSe14) (Tutorial SoSeS17)
  Material: SET1 , SET2, SET3 , SET4 , SET5, SET6

Publications

• Burdejova, P., Härdle, W. K., Kokoszka, P. and Q. Xiong (2017): Change point and trend analyses of annual expectile curves of tropical storms, Econometrics and Statistics DOI:10.1016/j.ecosta.2016.09.002

• Tran, N. M., Burdejova, P., Osipenko, M. and W. K. Härdle (2018): Principal Component Analysis in an Asymmetric Norm, Journal of Multivariate Analysis DOI: 10.1016/j.jmva.2018.10.004

• Burdejova, P. and W. K. Härdle (2017): Dynamic semi-parametric factor model for functional expectiles, SFB 649 Discussion Paper 2017-027 (revised)

Project Presentations

Principal components in asymmetric norm

Change point and trend test for expectiles of tropical storms

Brain and Risk Perception. Uncertainty and Complexity in Portfolio Decisions