In this paper, we develop robust estimation for the mean and covariance jointly for the regression model of longitudinal data within the framework of generalized estimating equations (GEE). The proposed approach integrates the robust method and joint mean–covariance regression modeling. Robust...

We consider asymptotic distributions of maximum deviations of sample covariance matrices, a fundamental problem in high-dimensional inference of covariances. Under mild dependence conditions on the entries of the data matrices, we establish the Gumbel convergence of the maximum deviations. Our...

It is well known that in a vector autoregressive (VAR) model Granger non-causality is characterized by a set of restrictions on the VAR coefficients. This characterization has been derived under the assumption of non-singularity of the covariance matrix of the innovations. This note shows that...

This paper considers the problem of estimating a covariance matrix under Stein’s loss. Sufficient conditions for the modified Efron–Morris estimator to be minimax under weighted quadratic loss are shown, which provide a general method for improving the estimator of the covariance matrix.

Differential entropy and log determinant of the covariance matrix of a multivariate Gaussian distribution have many applications in coding, communications, signal processing and statistical inference. In this paper we consider in the high-dimensional setting optimal estimation of the...

Several mathematical models have been proposed to predict the activation state of a transcription factor (TF) from the expression levels of its target genes. This inference problem is complicated however due to the fact that different genes may be regulated by different activation schemes...

This study seeks to explain economic growth differences in an aggregate production function framework, where labor reallocation from agriculture to modern sectors influences labor efficiency growth. The econometric analysis uses a panel of 65 countries over 1960-90. The results highlight: (a)...

This paper examines the empirical relationship between inequality and growth, and analyzes the impacts of growth, inequality, and government spending on poverty reduction. A new panel dataset has been assembled on inequality and poverty that reduces measurement error and ensures comparability...