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Modern Directional Statistics (Paperback)
Loot Price: R1,609
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Modern Directional Statistics (Paperback)
Series: Chapman & Hall/CRC Interdisciplinary Statistics
Expected to ship within 12 - 19 working days
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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. Christophe Ley is professor of
mathematical statistics at Ghent University. His research interests
include semi-parametrically efficient inference, flexible modeling,
directional statistics and the study of asymptotic approximations
via Stein's Method. His achievements include the Marie-Jeanne
Laurent-Duhamel prize of the Societe Francaise de Statistique and
an elected membership at the International Statistical Institute.
He is associate editor for the journals Computational Statistics
& Data Analysis and Econometrics and Statistics. Thomas
Verdebout is professor of mathematical statistics at Universite
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.
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