Li, Y., Datta, J., Craig, B. A. and Bhadra, A. (2019+). Joint Mean-Covariance Estimation via the Horseshoe with an Application in Genomic Data Analysis. (submitted).
 Li, Y., Craig, B. A. and Bhadra, A. (2019). The graphical horseshoe estimator for inverse covariance matrices. Journal of Computational and Graphical Statistics (to appear).
 Bhadra, A., Datta, J., Polson, N. G. and Willard, B. (2017). The horseshoe+ estimator of ultra-sparse signals. Bayesian Analysis 12, 1105–1131.
 Bhadra, A., Datta, J., Polson, N. G. and Willard, B. (2016). Default Bayesian analysis with global-local shrinkage priors. Biometrika 103, 955–969.
 Bhadra, A and Carroll, R. J. (2016). Exact sampling of the unobserved covariates in Bayesian spline models for measurement error problems. Statistics and Computing 26, 827-840.
 Feldman, G., Bhadra,
A. and Kirshner, S. (2014). Bayesian feature selection in high-dimensional regression in presence of correlated noise. Stat 3, 258-272.
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