63 citations · 113 across the 31 of their papers we have counts for
5 papers · 1 filter
Precision Matrix Estimation under the Horseshoe-like Prior-Penalty Dual
Ksheera Sagar, Sayantan Banerjee, Jyotishka Datta +1
Precision matrix estimation in a multivariate Gaussian model is fundamental to network estimation. Although there exist both Bayesian and frequentist approaches to this, it is diff…
Bayesian inference in high-dimensional models
Sayantan Banerjee, Ismaël Castillo, Subhashis Ghosal
Models with dimension more than the available sample size are now commonly used in various applications. A sensible inference is possible using a lower-dimensional structure. In re…
Bayesian Structure Learning in Graphical Models using Shrinkage priors
Sayantan Banerjee
We consider the problem of learning the structure of a high dimensional precision matrix under sparsity assumptions. We propose to use a shrinkage prior, called the DL-graphical pr…
Bayesian estimation of a sparse precision matrix
Sayantan Banerjee, Subhashis Ghosal
We consider the problem of estimating a sparse precision matrix of a multivariate Gaussian distribution, including the case where the dimension is large. Gaussian graphical mod…
Posterior convergence rates for estimating large precision matrices using graphical models
Sayantan Banerjee, Subhashis Ghosal
We consider Bayesian estimation of a precision matrix, when can be much larger than the available sample size . It is well known that consistent estimation in su…