Special Issue on "Advances in Multivariate Statistical Hypotheses Testing Methodologies"

This special issue focuses on recent methodological and theoretical advances in multivariate statistical hypothesis testing, covering both classical frameworks and new challenges arising from modern data environments. The aim is to bring together contributions that develop, analyze, or apply innovative testing procedures in multivariate settings.Topics of interest include, but are not limited to, parametric and non-parametric multivariate testing procedures, methods for high-dimensional data, and approaches designed for structured or non-Gaussian data. Contributions addressing theoretical developments, methodological innovations, and practical applications of multivariate hypothesis testing are particularly welcome. By bringing together researchers working on these topics, the special issue aims to highlight the current state of the art in multivariate hypothesis testing and to stimulate further developments and collaborations in this active research area.