118 citations · 351 across the 40 of their papers we have counts for
14 papers · 1 filter
Hyper-V uniform ergodicity of Markov chains
Austin Brown, Kshitij Khare
We develop a new uniform drift condition and local minorization that implies a stronger weighted form of uniform ergodicity for Markov chains we call hyper-V uniform ergodicity. Th…
Posterior consistency in multi-response regression models with non-informative priors for the error covariance matrix in growing dimensions
Partha Sarkar, Kshitij Khare, Malay Ghosh
The Inverse-Wishart (IW) distribution is a standard and popular choice of priors for covariance matrices and has attractive properties such as conditional conjugacy. However, the I…
Convergence properties of data augmentation algorithms for high-dimensional robit regression
Sourav Mukherjee, Kshitij Khare, Saptarshi Chakraborty
The logistic and probit link functions are the most common choices for regression models with a binary response. However, these choices are not robust to the presence of outliers/u…
Geometric ergodicity of Gibbs samplers for the Horseshoe and its regularized variants
Suman K. Bhattacharya, Kshitij Khare, Subhadip Pal
The Horseshoe is a widely used and popular continuous shrinkage prior for high-dimensional Bayesian linear regression. Recently, regularized versions of the Horseshoe prior have al…
Consistent Bayesian Sparsity Selection for High-dimensional Gaussian DAG Models with Multiplicative and Beta-mixture Priors
Xuan Cao, Kshitij Khare, Malay Ghosh
Estimation of the covariance matrix for high-dimensional multivariate datasets is a challenging and important problem in modern statistics. In this paper, we focus on high-dimensio…
A Hybrid Scan Gibbs Sampler for Bayesian Models with Latent Variables
Grant Backlund, James P. Hobert, Yeun Ji Jung +1
Gibbs sampling is a widely popular Markov chain Monte Carlo algorithm that can be used to analyze intractable posterior distributions associated with Bayesian hierarchical models.…