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  • Search: subject:"Large covariance matrix"
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Year of publication
Subject
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Large covariance matrix 6 Correlation 5 Estimation theory 5 Korrelation 5 Schätztheorie 5 Estimation 3 Schätzung 3 Time series analysis 3 Zeitreihenanalyse 3 ARCH model 2 ARCH-Modell 2 Analysis of variance 2 Factor analysis 2 Faktorenanalyse 2 Large correlation matrix 2 Multivariate Analyse 2 Multivariate analysis 2 Sparsity 2 Thresholding 2 Varianzanalyse 2 Volatility 2 Volatilität 2 Adaptive thresholding 1 Approximate factor model 1 Approximate factor models 1 Bernstein type inequality 1 Binary segmentation 1 CAPM 1 CUSUM 1 Correlation estimation 1 Covariance selection 1 Cross-section analysis 1 Dimension reduction 1 EM algorithm 1 Forecasting model 1 Hauptkomponentenanalyse 1 High-dimensional time series 1 Kalman filter 1 Kernel estimation 1 Large panels 1
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Online availability
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Undetermined 4 Free 2
Type of publication
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Article 6 Book / Working Paper 1
Type of publication (narrower categories)
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Article in journal 4 Aufsatz in Zeitschrift 4 Arbeitspapier 1 Graue Literatur 1 Non-commercial literature 1 Working Paper 1
Language
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English 5 Undetermined 2
Author
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Jiang, Binyan 2 Li, Degui 2 Fan, Jianqing 1 Fryzlewicz, Piotr 1 Hallin, Marc 1 Hotta, Luiz K. 1 Leng, Chenlei 1 Li, Yu-Ning 1 Liao, Yuan 1 Mazzeu, João H. G. 1 Pelagatti, Matteo 1 Peng, Bin 1 Pereira, Pedro L. Valls 1 Sbrana, Giacomo 1 Trucíos, Carlos 1 Wang, Hanchao 1 Yao, Jiawei 1 Zevallos, Mauricio 1
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Published in...
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Journal of business & economic statistics : JBES ; a publication of the American Statistical Association 2 Annals of the Institute of Statistical Mathematics 1 CefES paper series 1 Econometrica : journal of the Econometric Society, an internat. society for the advancement of economic theory in its relation to statistics and mathematics 1 Journal of econometrics 1 Statistics & Probability Letters 1
Source
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ECONIS (ZBW) 5 RePEc 2
Showing 1 - 7 of 7
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Detection of multiple structural breaks in large covariance matrices
Li, Yu-Ning; Li, Degui; Fryzlewicz, Piotr - In: Journal of business & economic statistics : JBES ; a … 41 (2023) 3, pp. 846-861
Persistent link: https://www.econbiz.de/10014448448
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Forecasting conditional covariance matrices in high-dimensional time series : a general dynamic factor approach
Trucíos, Carlos; Mazzeu, João H. G.; Hallin, Marc; … - In: Journal of business & economic statistics : JBES ; a … 41 (2023) 1, pp. 40-52
Persistent link: https://www.econbiz.de/10013540629
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Estimating high dimensional multivariate stochastic volatility models
Pelagatti, Matteo; Sbrana, Giacomo - 2020
Persistent link: https://www.econbiz.de/10012318391
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Nonparametric estimation of large covariance matrices with conditional sparsity
Wang, Hanchao; Peng, Bin; Li, Degui; Leng, Chenlei - In: Journal of econometrics 223 (2021) 1, pp. 53-72
Persistent link: https://www.econbiz.de/10012619958
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An empirical estimator for the sparsity of a large covariance matrix under multivariate normal assumptions
Jiang, Binyan - In: Annals of the Institute of Statistical Mathematics 67 (2015) 2, pp. 211-227
Large covariance or correlation matrix is frequently assumed to be sparse in that a number of the off-diagonal elements of the matrix are zero. This paper focuses on estimating the sparsity of a large population covariance matrix using a sample correlation matrix under multivariate normal...
Persistent link: https://www.econbiz.de/10011241462
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Power enhancement in high-dimensional cross-sectional tests
Fan, Jianqing; Liao, Yuan; Yao, Jiawei - In: Econometrica : journal of the Econometric Society, an … 83 (2015) 4, pp. 1497-1541
Persistent link: https://www.econbiz.de/10011405086
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Covariance selection by thresholding the sample correlation matrix
Jiang, Binyan - In: Statistics & Probability Letters 83 (2013) 11, pp. 2492-2498
This article shows that when the nonzero coefficients of the population correlation matrix are all greater in absolute value than (C1logp/n)1/2 for some constant C1, we can obtain covariance selection consistency by thresholding the sample correlation matrix. Furthermore, the rate (logp/n)1/2 is...
Persistent link: https://www.econbiz.de/10010709069
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