106 citations · 252 across the 33 of their papers we have counts for
13 papers · 1 filter
Bayesian Feature Extraction using Gaussian and Diffused-gamma Priors for High Dimensional Spatio-Temporal Data
Garrett Frady, Dipak K. Dey, Shariq Mohammed
High-dimensional data with sparse structure and spatio-temporal dependence arise in many scientific domains. We develop a Bayesian feature-extraction framework for spatio-temporal…
Interval Estimation of Coefficients in Penalized Regression Models of Insurance Data
Alokesh Manna, Zijian Huang, Dipak K. Dey +2
The Tweedie exponential dispersion family is a popular choice among many to model insurance losses that consist of zero-inflated semicontinuous data. In such data, it is often impo…
Bayesian Variable Selection in Double Generalized Linear Tweedie Spatial Process Models
Aritra Halder, Shariq Mohammed, Dipak K. Dey
Double generalized linear models provide a flexible framework for modeling data by allowing the mean and the dispersion to vary across observations. Common members of the exponenti…
Bayesian modeling with spatial curvature processes
Aritra Halder, Sudipto Banerjee, Dipak K. Dey
Spatial process models are widely used for modeling point-referenced variables arising from diverse scientific domains. Analyzing the resulting random surface provides deeper insig…
Generalized Co-sparse Factor Regression
Aditya Mishra, Dipak K. Dey, Yong Chen +1
Multivariate regression techniques are commonly applied to explore the associations between large numbers of outcomes and predictors. In real-world applications, the outcomes are o…
Approximate inferences for nonlinear mixed effects models with scale mixtures of skew-normal distributions
Fernanda L. Schumacher, Dipak K. Dey, Victor H. Lachos
Nonlinear mixed effects models have received a great deal of attention in the statistical literature in recent years because of their flexibility in handling longitudinal studies,…