The constraint that a covariance matrix must be positive definite presents difficulties for modeling its structure. Pourahmadi (1999, 2000) [18,19] proposed a parameterization of the covariance matrix for univariate longitudinal data in which the parameters are unconstrained, which is based on...

We consider the problem of testing whether a covariance matrix has a separable (Kronecker product) structure. Such structure is of particular interest when the observed variables can be cross-classified by two factors, as occurs for example when comparable or identical characteristics are...

Two asymptotic frameworks, increasing domain asymptotics and infill asymptotics, have been advanced for obtaining limiting distributions of maximum likelihood estimators of covariance parameters in Gaussian spatial models with or without a nugget effect. These limiting distributions are known to...

The bivariate Cramer--von Mises statistic has been proposed as a basis for goodness-of-fit testing for continuous bivariate distributions. This statistic can be expressed as the integral, over the unit square I2, of the square of the bivariate uniform empirical process. For some time it...