Large covariance and autocovariance matrices (Record no. 210711)

000 -LEADER
fixed length control field 01198cam a22003258i 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180608s2018 flu b 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781138303867
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 512.9434
Item number B6L2
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Bose, Arup,
9 (RLIN) 372640
245 ## - TITLE STATEMENT
Title Large covariance and autocovariance matrices
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc London
Name of publisher, distributor, etc CRC Press
Date of publication, distribution, etc 2019
300 ## - PHYSICAL DESCRIPTION
Extent xxiii, 272 p.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc Large Covariance and Autocovariance Matrices brings together a collection of recent results on sample covariance and autocovariance matrices in high-dimensional models and novel ideas on how to use them for statistical inference in one or more high-dimensional time series models. The prerequisites include knowledge of elementary multivariate analysis, basic time series analysis and basic results in stochastic convergence.

Part I is on different methods of estimation of large covariance matrices and auto-covariance matrices and properties of these estimators. Part II covers the relevant material on random matrix theory and non-commutative probability. Part III provides results on limit spectra and asymptotic normality of traces of symmetric matrix polynomial functions of sample auto-covariance matrices in high-dimensional linear time series models. These are used to develop graphical and significance tests for different hypotheses involving one or more independent high-dimensional linear time series.

The book should be of interest to people in econometrics and statistics (large covariance matrices and high-dimensional time series), mathematics (random matrices and free probability) and computer science (wireless communication). Parts of it can be used in post-graduate courses on high-dimensional statistical inference, high-dimensional random matrices and high-dimensional time series models. It should be particularly attractive to researchers developing statistical methods in high-dimensional time series models.

https://www.crcpress.com/Large-Covariance-and-Autocovariance-Matrices/Bose-Bhattacharjee/p/book/9781138303867
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical statistics
9 (RLIN) 372641
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Matrices
9 (RLIN) 372872
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Analysis of covariance
9 (RLIN) 372642
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Bhattacharjee, Monika
Relator term Co author
9 (RLIN) 372643
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 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 2019-01-01 6 7.00 1 512.9434 B6L2 198163 2020-04-03 2019-12-05 2019-12-05 8887.20 Books

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