Search Results - subject:"Spectral distribution"

Random matrix models for datasets with fixed time horizons

Zitelli, G. L. - In: Quantitative finance 20 (2020) 5, pp. 769-781

Persistent link: https://www.econbiz.de/10012262618

Cross-sectional independence test for a class of parametric panel data models

Pan, Guangming; Gao, Jiti; Yang, Yanrong; Guo, Meihui - 2015

Persistent link: https://www.econbiz.de/10011781344

On generalized expectation-based estimation of a population spectral distribution from high-dimensional data

Li, Weiming; Yao, Jianfeng - In: Annals of the Institute of Statistical Mathematics 67 (2015) 2, pp. 359-373

This paper discusses the problem of estimating the population spectral distribution from high-dimensional data. We …

Persistent link: https://www.econbiz.de/10011241461

Local expectations of the population spectral distribution of a high-dimensional covariance matrix

Li, Weiming - In: Statistical Papers 55 (2014) 2, pp. 563-573

This paper discusses the relationship between the population spectral distribution and the limit of the empirical … spectral distribution in high-dimensional situations. When the support of the limiting spectral distribution is split into … then used to analyze an estimator of the population spectral distribution in recent literature. Copyright Springer …

Persistent link: https://www.econbiz.de/10010794863

A Jarque-Bera test for sphericity of a large-dimensional covariance matrix

Glombek, Konstantin - 2013

This article provides a new test for sphericity of the covariance matrix of a d-dimensional multinormal population X ∼ Nd(µ,Σ). This test is applicable if the sample size, n + 1, and d both go to infinity while d/n → y ∈ (0,∞), provided that the limits of tr(Σk)/d, k = 1,...,8, are...

Persistent link: https://www.econbiz.de/10010312043

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

A Jarque-Bera test for sphericity of a large-dimensional covariance matrix

Glombek, Konstantin - Seminar für Wirtschafts- und Sozialstatistik, … - 2013

Persistent link: https://www.econbiz.de/10010986595

Testing Independence for a Large Number of High–Dimensional Random Vectors

Gao, Jiti; Pan, Guangming; Yang, Yanrong - Volkswirtschaftliche Fakultät, … - 2012

Persistent link: https://www.econbiz.de/10011259986

Independence Test for High Dimensional Random Vectors

Pan, G.; Gao, J.; Yang, Y.; Guo, M. - Department of Econometrics and Business Statistics, … - 2012

statistic is based on the characteristic function of the empirical spectral distribution of the sample covariance matrix. The …

Persistent link: https://www.econbiz.de/10009650288

Generalized cross-spectral test for nonlinear Granger causality with applications to money-output and price-volume relations

Li, Haiqi; Zhong, Wanling; Park, Sung Y. - In: Economic modelling 52 (2016), pp. 661-671

Persistent link: https://www.econbiz.de/10011642960