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Multivariate Nonparametric Methods with R - An approach based on spatial signs and ranks (Paperback, 2010 ed.)
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Multivariate Nonparametric Methods with R - An approach based on spatial signs and ranks (Paperback, 2010 ed.)
Series: Lecture Notes in Statistics, 199
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This book introduces a new way to analyze multivariate data. The
analysis of data based on multivariate spatial signs and ranks
proceeds very much as does a tra- tional multivariate analysis
relying on the assumption of multivariate normality: the L norm is
just replaced by different L norms, observation vectors are
replaced by 2 1 their(standardizedandcentered)spatial
signsandranks, andso on.Themethodsare fairly ef?cient and robust,
and no moment assumptions are needed. A uni?ed t- ory starting with
the simple one-sample location problem and proceeding through the
several-sample location problems to the general multivariate linear
regression model and ?nally to the analysis of cluster-dependent
data is presented. The material is divided into 14 chapters.
Chapter 1 serves as a short introd- tion to the general ideas and
strategies followed in the book. Chapter 2 introduces and discusses
different types of parametric, nonparametric, and semiparametric s-
tistical models used to analyze the multivariate data. Chapter 3
provides general descriptive tools to describe the properties of
multivariate distributions and mul- variate datasets. Multivariate
location and scatter functionals and statistics and their use is
described in detail. Chapter 4 introduces the concepts of
multivariate spatial sign, signed-rank, andrank, and shows their
connectionto certain L objectivefunc- 1 tions. Also sign and rank
covariance matrices are discussed carefully. The ?rst four chapters
thus provide the necessary tools to understand the remaining part
of the b
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