1 citations · 1 across the 3 of their papers we have counts for
3 papers
Bayesian adjustment for preferential testing in estimating the COVID-19 infection fatality rate
Harlan Campbell, Perry de Valpine, Lauren Maxwell +4
A key challenge in estimating the infection fatality rate (IFR) -- and its relation with various factors of interest -- is determining the total number of cases. The total number o…
Automatic adaptation of MCMC algorithms
Dao Nguyen, Perry de Valpine, Yves Atchade +3
Markov chain Monte Carlo (MCMC) methods are ubiquitous tools for simulation-based inference in many fields but designing and identifying good MCMC samplers is still an open questio…
Automated Parameter Blocking for Efficient Markov-Chain Monte Carlo Sampling
Daniel Turek, Perry de Valpine, Christopher J. Paciorek +1
Markov chain Monte Carlo (MCMC) sampling is an important and commonly used tool for the analysis of hierarchical models. Nevertheless, practitioners generally have two options for…