1.1k citations · 1.1k across the 5 of their papers we have counts for
5 papers
Computational methods for fast Bayesian model assessment via calibrated posterior p-values
Sally Paganin, Perry de Valpine
Posterior predictive p-values (ppps) have become popular tools for Bayesian model assessment, being general-purpose and easy to use. However, interpretation can be difficult becaus…
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…
Sequential Monte Carlo Methods in the nimble R Package
Nicholas Michaud, Perry de Valpine, Daniel Turek +2
nimble is an R package for constructing algorithms and conducting inference on hierarchical models. The nimble package provides a unique combination of flexible model specification…
Efficient Markov Chain Monte Carlo Sampling for Hierarchical Hidden Markov Models
Daniel Turek, Perry de Valpine, Christopher J. Paciorek
Traditional Markov chain Monte Carlo (MCMC) sampling of hidden Markov models (HMMs) involves latent states underlying an imperfect observation process, and generates posterior samp…
Programming with models: writing statistical algorithms for general model structures with NIMBLE
Perry de Valpine, Daniel Turek, Christopher J. Paciorek +3
We describe NIMBLE, a system for programming statistical algorithms for general model structures within R. NIMBLE is designed to meet three challenges: flexible model specification…