Generalized inferences about the mean vector of several multivariate Gaussian processes (Q1657895)

Summary: We consider in this paper the problem of comparing the means of several multivariate Gaussian processes. It is assumed that the means depend linearly on an unknown vector parameter \(\theta\) and that nuisance parameters appear in the covariance matrices. More precisely, we deal with the problem of testing hypotheses, as well as obtaining confidence regions for \(\theta\). Both methods will be based on the concepts of generalized \(p\) value and generalized confidence region adapted to our context.