The goal of this article is to test the hypothesis related to the independence of features
between any two repeated measures in a block compound symmetry structure under the …

The paper deals with the best unbiased estimators of the blocked compound symmetric
covariance structure for m-variate observations over u sites under the assumption of …

Testing hypotheses about the structure of a covariance matrix for doubly multivariate data is
often considered in the literature. In this paper the Rao's score test (RST) is derived to test …

A covariance matrix with a special pattern (eg, sparsity or block structure) is essential for
conducting multivariate analysis on high-dimensional data. Recently, a block covariance or …

One type of covariance structure is known as blocked compound symmetry. Recently, Roy et
al.(J Multivar Anal 144: 81–90, 2016) showed that, assuming this covariance structure …

The paper considers a high-dimensional likelihood ratio (LR) test on the block compound
symmetric (BCS) covariance structure of a multivariate Gaussian population. When the …

This article deals with the estimation and hypotheses testing problems for two-level and
three-level multivariate data. The coordinate-free approach is used to prove that the …

The popularity of the classical general linear model (CGLM) is attributable mostly to its ease
of fitting and validating; however, the CGLM is inappropriate for correlated observations. In …

The popularity of the classical general linear model (CGLM) is mostly due to the ease of
modeling and authentication of the appropriateness of the model. However, CGLM is not …

An extension of the D 2 test statistic to test the equality of mean for high-dimensional and k-
th order array-variate data using k-self similar compound symmetry (k-SSCS) covariance …