Multivariate statistical inference encompasses techniques for analysing and drawing conclusions from data in which multiple interrelated variables are observed simultaneously. Unlike univariate ...

Assessing multivariate normality is a fundamental prerequisite in many statistical analyses, including multivariate regression, principal component analysis and discriminant analysis. A broad spectrum ...

The goal of this talk is to familiarize those in attendance with some common multivariate methods, such as principal component analysis, factor analysis, Hotelling’s T 2, etc. We’ll try to motivate ...

Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variables under consideration. Multivariate analysis techniques may be used for several ...

Framework of DynIMTS. The model is a recurrent structure based on a spatial-temporal encoder and consists of three main components: embedding learning, spatial-temporal learning, and graph learning.