Search Results - subject:"Covariance matrix"

Hypothesis testing for high-dimensional covariance matrices

Li, Weiming; Qin, Yingli - In: Journal of Multivariate Analysis 128 (2014) C, pp. 108-119

Stieltjes transform of the spectral distribution of the sample covariance matrix. We prove that the proposed statistics are …

Persistent link: https://www.econbiz.de/10010776643

A quasi-maximum likelihood approach for integrated covariance matrix estimation with high frequency data

Liu, Cheng; Tang, Cheng Yong - In: Journal of Econometrics 180 (2014) 2, pp. 217-232

Estimating the integrated covariance matrix (ICM) from high frequency financial trading data is crucial to reflect the …

Persistent link: https://www.econbiz.de/10010776916

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 several intervals, the population one gains a meaningful...

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

Fast regularized canonical correlation analysis

Cruz-Cano, Raul; Lee, Mei-Ling Ting - In: Computational Statistics & Data Analysis 70 (2014) C, pp. 88-100

Canonical correlation analysis is a popular statistical method for the study of the correlations between two sets of variables. Finding the canonical correlations between these datasets requires the inversion of their corresponding sample correlation matrices. When the number of variables is...

Persistent link: https://www.econbiz.de/10010871476

Information Matrices and Standard Errors for MLEs of Item Parameters in IRT

Yuan, Ke-Hai; Cheng, Ying; Patton, Jeff - In: Psychometrika 79 (2014) 2, pp. 232-254

that is the middle piece of a sandwich-type covariance matrix. Monte Carlo results indicate that standard errors (SEs …. SEs based on the sandwich-type covariance matrix perform most consistently across conditions. Results also suggest that …-type covariance matrix or the observed information matrix. Copyright The Psychometric Society 2014 …

Persistent link: https://www.econbiz.de/10010848144

Limit theory for the largest eigenvalues of sample covariance matrices with heavy-tails

Davis, Richard A.; Pfaffel, Oliver; Stelzer, Robert - In: Stochastic Processes and their Applications 124 (2014) 1, pp. 18-50

We study the joint limit distribution of the k largest eigenvalues of a p×p sample covariance matrix XXT based on a …

Persistent link: https://www.econbiz.de/10011065005

Estimating high dimensional covariance matrices: A new look at the Gaussian conjugate framework

Hannart, Alexis; Naveau, Philippe - In: Journal of Multivariate Analysis 131 (2014) C, pp. 149-162

In this paper, we describe and study a class of linear shrinkage estimators of the covariance matrix that is well …

Persistent link: https://www.econbiz.de/10010930743

On the strong convergence of the optimal linear shrinkage estimator for large dimensional covariance matrix

Bodnar, Taras; Gupta, Arjun K.; Parolya, Nestor - In: Journal of Multivariate Analysis 132 (2014) C, pp. 215-228

In this work we construct an optimal linear shrinkage estimator for the covariance matrix in high dimensions. The … Frobenius loss over all linear shrinkage estimators for the covariance matrix. The case we consider includes the number of … covariance matrix tends almost surely to a deterministic quantity which can be consistently estimated. …

Persistent link: https://www.econbiz.de/10011041912

A new test for the proportionality of two large-dimensional covariance matrices

Liu, Baisen; Xu, Lin; Zheng, Shurong; Tian, Guo-Liang - In: Journal of Multivariate Analysis 131 (2014) C, pp. 293-308

Let X1,…,Xn1+1∼iidNp(μ1,Σ1) and Y1,…,Yn2+1∼iidNp(μ2,Σ2) be two independent random samples, where pn2. In this article, we propose a new test for the proportionality of two large p×p covariance matrices Σ1 and Σ2. By applying modern random matrix theory, we establish the asymptotic...

Persistent link: https://www.econbiz.de/10011041913

Asymptotic expansion for distribution of the trace of a covariance matrix under a two-step monotone incomplete sample

Tsukada, Shin-ichi - In: Journal of Multivariate Analysis 129 (2014) C, pp. 206-219

The covariance matrix is embedded in several statistics (such as the trace and general variance) of multivariate … statistical analysis. We investigate the trace of the covariance matrix in the context of a two-step monotone incomplete sample … drawn from Np+q(μ,Σ), a multivariate normal population with mean μ and covariance matrix Σ. Since there are the maximum …

Persistent link: https://www.econbiz.de/10011041982