In this paper, a shrinkage estimator for the population mean is proposed under known quadratic loss functions with unknown covariance matrices. The new estimator is non-parametric in the sense that it does not assume a specific parametric distribution for the data and it does not require the...

Measures of association are suggested between two random vectors. The measures are copula-based and therefore invariant with respect to the univariate marginal distributions. The measures are able to capture positive as well as negative association. In case the random vectors are just random...

The multivariate two-sample testing problem has been well investigated in the literature, and several parametric and nonparametric methods are available for it. However, most of these two-sample tests perform poorly for high dimensional data, and many of them are not applicable when the...