most citedBayesian variable selection in linear regression models with instrumental variables

1 citations · 1 across the 1 of their papers we have counts for

collaborators

3 papers

stat.CO2019

Markov chain Monte Carlo algorithms with sequential proposals

Joonha Park, Yves F. Atchadé

We explore a general framework in Markov chain Monte Carlo (MCMC) sampling where sequential proposals are tried as a candidate for the next state of the Markov chain. This sequenti…

stat.CO2019

Approximate spectral gaps for Markov chains mixing times in high dimensions

Yves F. Atchadé

This paper introduces a concept of approximate spectral gap to analyze the mixing time of Markov Chain Monte Carlo (MCMC) algorithms for which the usual spectral gap is degenerate…

stat.ME2019★ 1 cited

Bayesian variable selection in linear regression models with instrumental variables

Gautam Sabnis, Yves Atchadé, Prosper Dovonon

Many papers on high-dimensional statistics have proposed methods for variable selection and inference in linear regression models by relying explicitly or implicitly on the assumpt…