Statistical Analysis for High Dimensional Data is popular PDF and ePub book, written by Arnoldo Frigessi in 2016-02-16, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Statistical Analysis for High Dimensional Data can be Read Online from any device for your convenience.
Statistical Analysis for High Dimensional Data Book PDF Summary
This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, 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.
Detail Book of Statistical Analysis for High Dimensional Data PDF
- Author : Arnoldo Frigessi
- Release : 16 February 2016
- Publisher : Springer
- ISBN : 9783319270999
- Genre : Mathematics
- Total Page : 306 pages
- Language : English
- PDF File Size : 18,9 Mb
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