Applied Directional Statistics : Modern Methods and Case Studies

Christophe Ley

ISBN 10: 1138626430 / ISBN 13: 9781138626430

Published by CRC Press Sep 2018, 2018

About this Item

Neuware - This book collects important advances in methodology and data analysis for directional statistics. It is the companion book of the more theoretical treatment presented in Modern Directional Statistics (CRC Press, 2017). The field of directional statistics has received a lot of attention due to demands from disciplines such as life sciences or machine learning, the availability of massive data sets requiring adapted statistical techniques, and technological advances. This book covers important progress in bioinformatics, biology, astrophysics, oceanography, environmental sciences, earth sciences, machine learning and social sciences.

Seller Inventory # 9781138626430

Bibliographic Details

• Title: Applied Directional Statistics : Modern Methods and Case Studies
• Publisher: CRC Press Sep 2018
• Publication Date: 2018
• Language: English
• ISBN 10: 1138626430
• ISBN 13: 9781138626430
• Binding: Buch
• Condition: Neu
• Dimensions: 236W x 158H x 22D millimeters 236 millimeters width by 158 millimeters height by 22 millimeters depth
• Weight: 635 grams

About this title

Synopsis

This book collects important advances in methodology and data analysis for directional statistics. It is the companion book of the more theoretical treatment presented in Modern Directional Statistics (CRC Press, 2017). The field of directional statistics has received a lot of attention due to demands from disciplines such as life sciences or machine learning, the availability of massive data sets requiring adapted statistical techniques, and technological advances. This book covers important progress in bioinformatics, biology, astrophysics, oceanography, environmental sciences, earth sciences, machine learning and social sciences.

About the Author

Christophe Ley is professor of mathematical statistics at Ghent University. His research interests include semi-parametrically efficient inference, flexible modeling, directional statistics, sport statistics and the study of asymptotic approximations via Stein’s Method. His achievements include the Marie-Jeanne Laurent-Duhamel prize of the Société Française de Statistique and an elected membership of the International Statistical Institute. He is associate editor for the journals Computational Statistics & Data Analysis, Annals of the Institute of Statistical Mathematics, and Econometrics and Statistics.

Thomas Verdebout is professor of mathematical statistics at Université libre de Bruxelles (ULB). His main research interests are semi-parametric statistics, high-dimensional statistics, directional statistics and rank-based procedures. He has won an annual prize of the Belgian Academy of Sciences and is an elected member of the International Statistical Institute. He is associate editor for the journals Statistics and Probability Letters and Journal of Multivariate Analysis.