21 citations · 52 across the 19 of their papers we have counts for
20 papers
A Novel Class of Unfolding Models for Binary Preference Data
Rayleigh Lei, Abel Rodriguez
We develop a new class of spatial voting models for binary preference data that can accommodate both monotonic and non-monotonic response functions, and are more flexible than alte…
Dynamic Factor Models for Binary Data in Circular Spaces: An Application to the U.S. Supreme Court
Rayleigh Lei, Abel Rodriguez
Latent factor models are widely used in the social and behavioral science as scaling tools to map discrete multivariate outcomes into low dimensional, continuous scales. In politic…
Laplace Power-expected-posterior priors for generalized linear models with applications to logistic regression
Anupreet Porwal, Abel Rodriguez
Power-expected-posterior (PEP) methodology, which borrows ideas from the literature on power priors, expected-posterior priors and unit information priors, provides a systematic wa…
Computational strategies and estimation performance with Bayesian semiparametric Item Response Theory models
Sally Paganin, Christopher J. Paciorek, Claudia Wehrhahn +3
Item response theory (IRT) models typically rely on a normality assumption for subject-specific latent traits, which is often unrealistic in practice. Semiparametric extensions bas…
High Dimensional Bayesian Network Classification with Network Global-Local Shrinkage Priors
Sharmistha Guha, Abel Rodriguez
This article proposes a novel Bayesian classification framework for networks with labeled nodes. While literature on statistical modeling of network data typically involves analysi…
A Bayesian Approach to Spherical Factor Analysis for Binary Data
Xingchen Yu, Abel Rodriguez
Factor models are widely used across diverse areas of application for purposes that include dimensionality reduction, covariance estimation, and feature engineering. Traditional fa…