Sufficient dimension reduction: methods and applications with R (Record no. 210701)

000 -LEADER
fixed length control field aam a22 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190116b2018 ||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781498704472
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Item number L4S8
Classification number 519.536
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Li, Bing
9 (RLIN) 373481
245 ## - TITLE STATEMENT
Title Sufficient dimension reduction: methods and applications with R
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc CRC Press
Date of publication, distribution, etc 2018
Place of publication, distribution, etc London
300 ## - PHYSICAL DESCRIPTION
Extent xxi, 283 p.
Other physical details With index
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Monographs on statistics and applied probability 161
9 (RLIN) 373496
520 ## - SUMMARY, ETC.
Summary, etc Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of variables. Sufficient Dimension Reduction: Methods and Applications with R introduces the basic theories and the main methodologies, provides practical and easy-to-use algorithms and computer codes to implement these methodologies, and surveys the recent advances at the frontiers of this field.

Features

Provides comprehensive coverage of this emerging research field.
Synthesizes a wide variety of dimension reduction methods under a few unifying principles such as projection in Hilbert spaces, kernel mapping, and von Mises expansion.
Reflects most recent advances such as nonlinear sufficient dimension reduction, dimension folding for tensorial data, as well as sufficient dimension reduction for functional data.
Includes a set of computer codes written in R that are easily implemented by the readers.
Uses real data sets available online to illustrate the usage and power of the described methods.

Sufficient dimension reduction has undergone momentous development in recent years, partly due to the increased demands for techniques to process high-dimensional data, a hallmark of our age of Big Data. This book will serve as the perfect entry into the field for the beginning researchers or a handy reference for the advanced ones.

https://www.crcpress.com/Sufficient-Dimension-Reduction-Methods-and-Applications-with-R/Li/p/book/9781498704472
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Dimension reduction
9 (RLIN) 373492
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistics - Data processing
9 (RLIN) 373493
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Regression analysis - Data processing
9 (RLIN) 373494
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element R - Computer program language
9 (RLIN) 373495
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Permanent location Current location Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Total Renewals Full call number Barcode Checked out Date last seen Date last borrowed Cost, replacement price Koha item type
          Non-fiction Vikram Sarabhai Library Vikram Sarabhai Library General Stacks 2019-01-28 5 5.00 2 3 519.536 L4S8 198243 2019-08-15 2019-04-17 2019-04-17 7199.50 Books

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