Wolfgang Karl Härdle is the Ladislaus von Bortkiewicz Professor of Statistics at the Humboldt-Universität zu Berlin and Director of C.A.S.E. (Center for Applied Statistics and Economics), Director of the CRC-649 (Collaborative Research Center) "Economic Risk" as well as Director of the IRTG 1792 "High Dimensional Non-stationary Time Series". He teaches quantitative finance and semi-parametric statistics. His research focuses on dynamic factor models, multivariate statistics, tail event curves in finance and computational statistics. He is an elected member of the ISI (International Statistical Institute) and foreign expert professor at Xiamen University, China, and a senior fellow of Sim Kee Boon Institute of Financial Economics at the Singapore Management University.

Ostap Okhrin is Professor of Econometrics and Statistics, especially in Transportation at the Dresden University of Technology. He worked at the European University Viadrin

Yarema Okhrin is Professor of Statistics at the University of Augsburg. He teaches financial econometrics and multivariate data analysis. His research focuses on multivariate statistics and econometrics with applications to finance, statistical surveillance and computational statistics. He previously worked as Assistant Professor of Econometrics at the University of Bern and at the European University Viadrina.

Covers basic mathematical, statistical and programming problems in computational statistics

Addresses both univariate and multivariate statistical data analysis and applications in finance, the life sciences and other disciplines

Features R sniplets in the text and computer programs on GitHub that allow all examples to be fully reproduced

Provides a smooth introduction to R for statistical computing

The Basics of R.- Numerical Techniques.- Combinatorics and Discrete Distributions.- Univariate Distributions.- Univariate Statistical Analysis.- Basic Nonparametric Methods.- Multivariate Distributions.- Multivariate Statistical Analysis.- Random Numbers in R.- Advanced Graphical Techniques in R.- Symbols and Notations.