We introduce a flexible parametric family of matrix-valued covariance functions for multivariate spatial random fields, where each constituent component is a Matérn process. The model parameters are ...

The authors advocate the use of the generalized variance of the sample means-the determinant of the variance-covariance matrix $D(\overline{y})$ of the means-as a ...

Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...

Multivariate analyses using nonimaging and neuroimaging delivered a more accurate characterization of the link between brain variations and psychosis, demonstrating that general intelligence, BMI, ...