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

Multivariate methods are known to increase the statistical power to detect associations in the case of shared genetic basis between phenotypes. They have, however, lacked essential analytic tools to ...

1. Aspects of multivariate analysis -- 2. Matrix algebra and random vectors -- 3. Sample geometry and random sampling -- 4. The multivariate normal distribution -- 5. Inferences about a mean vector -- ...

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.