Objectives This study uses nationally representative survey data from the USA to estimate the relationship between a history of heart attack or stroke with the prevalence of mental health symptoms.

This paper addresses these issues by developing a novel generalized Bayesian inference approach tailored for regression models with intractable likelihoods. The key idea is to employ a specific form ...

APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering ...

We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be modeled ...

Here, we propose a two-step generalized regression model with regularization for dealing with collinearity when developing linear prediction models. The model first reduces dimensionality of the ...

This paper is reports an extension of our previous investigations on adding transparency to neural networks. We focus on a class of linear priors (LPs), such as symmetry, ranking list, boundary, ...

We apply this framework to generalized linear models, where we propose various strategies for the specification of a tuning parameter governing the degree of shrinkage and study resultant theoretical ...