000 04710nam a2200409Ii 4500
001 9780203730652
008 180727s2018 flu b ob 001 0 eng d
020 _a9780203730652
_q(e-book : PDF)
035 _a(OCoLC)1044733965
040 _aFlBoTFG
_cFlBoTFG
_erda
050 4 _aQA188
072 7 _aMAT
_x029000
_2bisacsh
072 7 _aMAT
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_2bisacsh
072 7 _aPBT
_2bicscc
082 0 4 _a512.9/434
_223
100 1 _aBose, Arup,
_eauthor.
_910714
245 1 0 _aLarge covariance and autocovariance matrices /
_cby Arup Bose and Monika Bhattacharjee.
250 _aFirst edition.
264 1 _aBoca Raton, FL :
_bChapman and Hall/CRC, an imprint of Taylor and Francis,
_c2018.
300 _a1 online resource (296 pages).
336 _atext
_2rdacontent
337 _acomputer
_2rdamedia
338 _aonline resource
_2rdacarrier
490 1 _aChapman & Halll/CRC monographs on statistics & applied probability
505 0 _apart 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 _aLarge 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.
650 0 _aAnalysis of covariance.
_910715
650 0 _aMatrices.
_92259
650 7 _aMATHEMATICS / Algebra / Intermediate.
_2bisacsh
_910716
650 7 _aMATHEMATICS / Probability & Statistics / Bayesian Analysis.
_2bisacsh
_910717
700 1 _aBhattacharjee, Monika,
_eauthor.
_910718
710 2 _aTaylor and Francis.
_910719
776 0 8 _iPrint version:
_z9781138303867
830 0 _aChapman & Halll/CRC monographs on statistics & applied probability.
_910720
856 4 0 _uhttps://www.taylorfrancis.com/books/9780203730652
_zClick here to view.
942 _cEBK
999 _c69786
_d69786