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  • Search: subject:"Large dimensional sample covariance matrix"
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Year of publication
Subject
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Central limit theorem 2 Covariance stationary time series 2 Empirical spectral distribution 2 Independence test 2 Large dimensional sample covariance matrix 2 Linear spectral statistics 2
Online availability
All
Free 2
Type of publication
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Book / Working Paper 2
Language
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Undetermined 2
Author
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Gao, Jiti 2 Pan, Guangming 2 Yang, Yanrong 2
Institution
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Department of Econometrics and Business Statistics, Monash Business School 1 Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München 1
Published in...
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MPRA Paper 1 Monash Econometrics and Business Statistics Working Papers 1
Source
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RePEc 2
Showing 1 - 2 of 2
Cover Image
Testing Independence for a Large Number of High Dimensional Random Vectors
Pan, Guangming; Gao, Jiti; Yang, Yanrong - Department of Econometrics and Business Statistics, … - 2013
Capturing dependence among a large number of high dimensional random vectors is a very important and challenging problem. By arranging n random vectors of length p in the form of a matrix, we develop a linear spectral statistic of the constructed matrix to test whether the n random vectors are...
Persistent link: https://www.econbiz.de/10010860404
Saved in:
Cover Image
Testing Independence for a Large Number of High–Dimensional Random Vectors
Gao, Jiti; Pan, Guangming; Yang, Yanrong - Volkswirtschaftliche Fakultät, … - 2012
Capturing dependence among a large number of high dimensional random vectors is a very important and challenging problem. By arranging n random vectors of length p in the form of a matrix, we develop a linear spectral statistic of the constructed matrix to test whether the n random vectors are...
Persistent link: https://www.econbiz.de/10011259986
Saved in:
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