Spatial probit generalized linear mixed models (spGLMM) with a linear fixed effect and a
spatial random effect, endowed with a Gaussian Process prior, are widely used for analysis …

Correlated binary response data with covariates are ubiquitous in longitudinal or spatial
studies. Among the existing statistical models, the most well‐known one for this type of data …

We develop two statistical models for space-time abundance data based on a stochastic
underlying continuous individual movement. In contrast to current models for abundance in …

Tile low rank representations of dense matrices partition them into blocks of roughly uniform
size, where each off-diagonal tile is compressed and stored as its own low rank factorization …

We present the features and implementation of the R package nvmix for the class of normal
variance mixtures including Student t and normal distributions. The package provides …

Multivariate normal (MVN) probabilities arise in myriad applications, but they are analytically
intractable and need to be evaluated via Monte-Carlo-based numerical integration. For the …

Addressing the statistical challenge of computing the multivariate normal (MVN) probability
in high dimensions holds significant potential for enhancing various applications. One …

The thesis concerns the analysis of correlated data on multiple variables via the EM
algorithm and its variants. Specifically, we focus on (cross-sectional) multivariate iid data …

This dissertation contains four projects involving applications of truncated multivariate
normal sampling and multivariate normal probability estimation for linearly constrained …

This case study provides information about computing (approximating) likelihoods of
structural equation models with ordinal variables. We consider interactions between …