Multivariate spatial regression models

Multivariate Spatial Process Models

Multivariate Functional Regression Models for Epistasis Analysis

To date, most genetic analyses of phenotypes have focused on analyzing single traits or, analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power, and hold the key to understanding the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex tra...

Outlier Detection Methods in Multivariate Regression Models

Outlier detection statistics based on two models, the case-deletion model and the mean-shift model, are developed in the context of a multivariate linear regression model. These are generalizations of the univariate Cook’s distance and other diagnostic statistics. Approximate distributions of the proposed statistics are also obtained to get suitable cutoff points for significance tests. In addi...

Multivariate Frequency-Severity Regression Models in Insurance

In insurance and related industries including healthcare, it is common to have several outcome measures that the analyst wishes to understand using explanatory variables. For example, in automobile insurance, an accident may result in payments for damage to one’s own vehicle, damage to another party’s vehicle, or personal injury. It is also common to be interested in the frequency of accidents ...

Structured covariance matrices in multivariate regression models

A similarity matrix is a covariance matrix generated by additive nested common factors having independent components. The set of such matrices is a structured subset of covariance matrices, closed under permutation and restriction, which makes it potentially useful as a sub-model for the joint dependence of several responses. It is also equal to the set of rooted trees. Some issues connected wi...