Reference : Modern Directional Statistics
Books : Collective work published as editor or director
Physical, chemical, mathematical & earth Sciences : Mathematics
Modern Directional Statistics
Ley, Christophe mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Mathematics (DMATH) >]
Verdebout, Thomas mailto [Université Libre de Bruxelles - ULB > Faculté des Sciences]
Chapman and Hall/CRC
[en] Modern Directional Statistics collects important advances in methodology and theory for directional statistics over the last two decades. It provides a detailed overview and analysis of recent results that can help both researchers and practitioners. Knowledge of multivariate statistics eases the reading but is not mandatory.

The field of directional statistics has received a lot of attention over the past two decades, due to new demands from domains such as life sciences or machine learning, to the availability of massive data sets requiring adapted statistical techniques, and to technological advances. This book covers important progresses in distribution theory, high-dimensional statistics, kernel density estimation, efficient inference on directional supports, and computational and graphical methods.
Researchers ; Professionals ; Students ; General public,help%20both%20researchers%20and%20practitioners.
"The book is definitely handy for researchers and graduate students in statistics as well as for scientists and practical users in bioscience, ecological and environmental sciences, social sciences and other applied areas where directional data analysis is needed and even high-dimensional data analytics is encountered." ~Shuangzhe Liu, Stat Papers

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