Large covariance and autocovariance matrices / (Record no. 69786)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04710nam a2200409Ii 4500 |
| 001 - CONTROL NUMBER | |
| control field | 9780203730652 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 180727s2018 flu b ob 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780203730652 |
| -- | (e-book : PDF) |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 512.9/434 |
| 100 1# - AUTHOR NAME | |
| Author | Bose, Arup, |
| 245 10 - TITLE STATEMENT | |
| Title | Large covariance and autocovariance matrices / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | First edition. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 online resource (296 pages). |
| 490 1# - SERIES STATEMENT | |
| Series statement | Chapman & Halll/CRC monographs on statistics & applied probability |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 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. |
| 520 3# - 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.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 and 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. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Bhattacharjee, Monika, |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://www.taylorfrancis.com/books/9780203730652 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Boca Raton, FL : |
| -- | Chapman and Hall/CRC, an imprint of Taylor and Francis, |
| -- | 2018. |
| 336 ## - | |
| -- | text |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | rdacarrier |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Analysis of covariance. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Matrices. |
| 650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | MATHEMATICS / Algebra / Intermediate. |
| 650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | MATHEMATICS / Probability & Statistics / Bayesian Analysis. |
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