Statistical Analysis for High-Dimensional Data

The Abel Symposium 2014

Autor: Arnoldo Frigessi, Peter Bühlmann, Ingrid Glad, Mette Langaas, Sylvia Richardson, Marina Vannucci

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Legare: Copertă tare

Editura: Springer International Publishing AG

Disponibilitate: În depozitul extern

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This book features research contributions from The Abel Symposium on Statistical Analys...

Informații despre carte

Autor

Arnoldo Frigessi, Peter Bühlmann, Ingrid Glad, Mette Langaas, Sylvia Richardson, Marina Vannucci

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2016

Pagini

306

EAN

9783319270975

ISBN

3319270974

Enbook ID

02832972

Editura

Springer International Publishing AG

Greutate

6033

Dimensiuni

155 x 235 x 23

Descriere completă

This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvĺgar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in "big data" situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on future research directions, the contributions will benefit graduate students and researchers in computational biology, statistics and the machine learning community.

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Statistical Analysis for High-Dimensional Data

The Abel Symposium 2014

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