Yarema Okhrin – författare

This book presents a unique collection of contributions on modern methods and applications in three key areas of statistics, celebrating the significant work of Wolfgang Schmid in this field. It is structured thematically into parts focusing on statistical process monitoring, financial statistics, and spatial statistics with environmetrics, each featuring chapters from leading experts.

The opening articles on statistical process monitoring present novel methodologies for the detection of anomalies and control charting techniques, which are crucial for maintaining quality in manufacturing processes. Detailed discussions are included on integrating multivariate statistical methods and real-time monitoring to enhance process reliability and efficiency.

The part on financial statistics explores rigorous approaches in financial econometrics, with an emphasis on dynamic modelling of market volatility and risk assessment. Contributions cover advanced asset allocation strategies, leveraging high-dimensional data analysis, and the application of machine learning techniques.

Spatial statistics and environmetrics are addressed through innovative research on the statistical analysis of environmental data. This includes the use of geostatistical models and hybrid models that combine traditional statistical techniques with machine learning to improve the prediction of environmental phenomena. Key topics here involve the modelling of extremes and airborne pollutants, the prediction of earthquakes using a smartphone-based sensor network, and reviews of selected topics essential in modern spatial statistics.

Each part not only reflects Wolfgang Schmid’s interests and impact in these areas but also provides detailed theoretical and applied studies, demonstrating how these sophisticated statistical methods can be effectively employed in practical scenarios. This makes the book an indispensable resource for researchers and practitioners looking to apply cutting-edge statistical techniques in these complex fields.

This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. It covers mathematical, statistical as well as programming problems in computational statistics and contains a wide variety of practical examples. In addition to the numerous R sniplets presented in the text, all computer programs (quantlets) and data sets to the book are available on GitHub and referred to in the book. This enables the reader to fully reproduce as well as modify and adjust all examples to their needs.

The book is intended for advanced undergraduate and first-year graduate students as well as for data analysts new to the job who would like a tour of the various statistical tools in a data analysis workshop. The experienced reader with a good knowledge of statistics and programming might skip some sections on univariate models and enjoy the various ma

The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web.  QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.