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عنوان
Large covariance and autocovariance matrices /

پدید آورنده
Arup Bose, Monika Bhattacharjee.

موضوع
Analysis of covariance.,Matrices.,Analysis of covariance.,MATHEMATICS / Algebra / Intermediate,Matrices.

رده
QA188
.
B6735
2018eb

کتابخانه
Center and Library of Islamic Studies in European Languages

محل استقرار
استان: Qom ـ شهر: Qom

Center and Library of Islamic Studies in European Languages

تماس با کتابخانه : 32910706-025

INTERNATIONAL STANDARD BOOK NUMBER

(Number (ISBN
0203730658
(Number (ISBN
1351398164
(Number (ISBN
9780203730652
(Number (ISBN
9781351398169
Erroneous ISBN
1138303860
Erroneous ISBN
9781138303867

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
Large covariance and autocovariance matrices /
General Material Designation
[Book]
First Statement of Responsibility
Arup Bose, Monika Bhattacharjee.

.PUBLICATION, DISTRIBUTION, ETC

Place of Publication, Distribution, etc.
Boca Raton :
Name of Publisher, Distributor, etc.
CRC Press, Taylor & Francis Group,
Date of Publication, Distribution, etc.
2018.

PHYSICAL DESCRIPTION

Specific Material Designation and Extent of Item
1 online resource.

SERIES

Series Title
Chapman & Halll/CRC monographs on statistics & applied probability

INTERNAL BIBLIOGRAPHIES/INDEXES NOTE

Text of Note
Includes bibliographical references and index.

CONTENTS NOTE

Text of Note
Part Part I -- chapter 1 LARGE COVARIANCE MATRIX I -- chapter 2 LARGE COVARIANCE MATRIX II -- chapter 3 LARGE AUTOCOVARIANCE MATRIX -- part Part II -- chapter 4 SPECTRAL DISTRIBUTION -- chapter 5 NON-COMMUTATIVE PROBABILITY -- chapter 6 GENERALIZED COVARIANCE MATRIX I -- chapter 7 GENERALIZED COVARIANCE MATRIX II -- part Part III -- chapter 8 SPECTRA OF AUTOCOVARIANCE MATRIX I -- chapter 9 SPECTRA OF AUTOCOVARIANCE MATRIX II -- chapter 10 GRAPHICAL INFERENCE -- chapter 11 TESTING WITH TRACE.
0

SUMMARY OR ABSTRACT

Text of Note
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.Arup Bose is a professor at the Indian Statistical Institute, Kolkata, India. He is a distinguished researcher in mathematical statistics and has been working in high-dimensional random matrices for the last fifteen years. He has been editor of Sankhy? for several years and has been on the editorial board of several other journals. He is a Fellow of the Institute of Mathematical Statistics, USA and all three national science academies of India, as well as the recipient of the S.S. Bhatnagar Award and the C.R. Rao Award. His first book Patterned Random Matrices was also published by Chapman & Hall. He has a forthcoming graduate text U-statistics, M-estimates and Resampling (with Snigdhansu Chatterjee) to be published by Hindustan Book Agency. Monika Bhattacharjee is a post-doctoral fellow at the Informatics Institute, University of Florida. After graduating from St. Xavier's College, Kolkata, she obtained her master's in 2012 and PhD in 2016 from the Indian Statistical Institute. Her thesis in high-dimensional covariance and auto-covariance matrices, written under the supervision of Dr. Bose, has received high acclaim.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.

OTHER EDITION IN ANOTHER MEDIUM

Title
Large covariance and autocovariance matrices.
International Standard Book Number
9781138303867

TOPICAL NAME USED AS SUBJECT

Analysis of covariance.
Matrices.
Analysis of covariance.
MATHEMATICS / Algebra / Intermediate
Matrices.

(SUBJECT CATEGORY (Provisional

MAT-- 002040
PBT

DEWEY DECIMAL CLASSIFICATION

Number
512
.
9/434
Edition
23

LIBRARY OF CONGRESS CLASSIFICATION

Class number
QA188
Book number
.
B6735
2018eb

PERSONAL NAME - PRIMARY RESPONSIBILITY

Bose, Arup

PERSONAL NAME - ALTERNATIVE RESPONSIBILITY

Bhattacharjee, Monika

ORIGINATING SOURCE

Date of Transaction
20200822180017.0
Cataloguing Rules (Descriptive Conventions))
pn

ELECTRONIC LOCATION AND ACCESS

Electronic name
 مطالعه متن کتاب 

[Book]

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