58 citations · 198 across the 19 of their papers we have counts for
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Coupling-based convergence assessment of some Gibbs samplers for high-dimensional Bayesian regression with shrinkage priors
Niloy Biswas, Anirban Bhattacharya, Pierre E. Jacob +1
We consider Markov chain Monte Carlo (MCMC) algorithms for Bayesian high-dimensional regression with continuous shrinkage priors. A common challenge with these algorithms is the ch…
Scaling up Data Augmentation MCMC via Calibration
Leo L. Duan, James E. Johndrow, David B. Dunson
There has been considerable interest in making Bayesian inference more scalable. In big data settings, most literature focuses on reducing the computing time per iteration, with le…
Estimating the observable population size from biased samples: a new approach to population estimation with capture heterogeneity
James E. Johndrow, Kristian Lum, Daniel Manrique-Vallier
Capture-recapture methods aim to estimate the size of a closed population on the basis of multiple incomplete enumerations of individuals. In many applications, the individual prob…
Optimal Gaussian approximations to the posterior for log-linear models with Diaconis-Ylvisaker priors
James E. Johndrow, Anirban Bhattacharya
In contingency table analysis, sparse data is frequently encountered for even modest numbers of variables, resulting in non-existence of maximum likelihood estimates. A common solu…