Subhashis Ghoshal

Projection-posterior for variable selection: Weak limit and coverage

Pal, S., & Ghosal, S. (2025, January 1). Electronic Journal of Statistics, Vol. 19, pp. 3743–3770.

Editorial Article: Remembering D. Basu’s Legacy in Statistics

Dey, D., Ghosal, S., & Samanta, T. (2024, November 1). Sankhya A, Vol. 11.

Combining phenotypic and genomic data to improve prediction of binary traits

Jarquin, D., Roy, A., Clarke, B., & Ghosal, S. (2023, May 16). Journal of Applied Statistics.

Posterior contraction and testing for multivariate isotonic regression

Wang, K., & Ghosal, S. (2023, January 1). Electronic Journal of Statistics, Vol. 17, pp. 798–822.

Discussion of “Confidence Intervals for Nonparametric Empirical Bayes Analysis” by Ignatiadis and Wager

Ghosal, S. (2022, July 3). Journal of the American Statistical Association, Vol. 117, pp. 1171–1174.

Rates and coverage for monotone densities using projection-posterior

Chakraborty, M., & Ghosal, S. (2022, March 4). Bernoulli, Vol. 28, pp. 1093–1119.

Two-step Bayesian methods for generalized regression driven by partial differential equations

Bhaumik, P., Shi, W., & Ghosal, S. (2022, April 25). Bernoulli, Vol. 28, pp. 1625–1647.

Bayesian estimation of sparse precision matrices in the presence of Gaussian measurement error

Shi, W., Ghosal, S., & Martin, R. (2021, January 1). Electronic Journal of Statistics.

Bayesian multivariate quantile regression using Dependent Dirichlet Process prior

Bhattacharya, I., & Ghosal, S. (2021, April 30). Journal of Multivariate Analysis.

Unified Bayesian theory of sparse linear regression with nuisance parameters

Jeong, S., & Ghosal, S. (2021, January 1). Electronic Journal of Statistics, Vol. 15, pp. 3040–3111.

Bayesian Inference on Multivariate Medians and Quantiles

Bhattacharya, I., & Ghosal, S. (2020, August 4). Statistica Sinica, Vol. 32, pp. 517–538.

Bayesian linear regression for multivariate responses under group sparsity

Ning, B., Jeong, S., & Ghosal, S. (2020, April 27). Bernoulli, Vol. 26, pp. 2353–2382.

Coverage of Bayesian credible intervals for monotone regression

Annals of Statistics.

Empirical Bayes oracle uncertainty quantification for regression

The Annals of Statistics.

Posterior contraction and credible sets for filaments of regression functions

Li, W., & Ghosal, S. (2020, January 1). Electronic Journal of Statistics, Vol. 14, pp. 1707–1743.

Posterior contraction in sparse generalized linear models

Jeong, S., & Ghosal, S. (2020, September 1). Biometrika, Vol. 9, pp. 367–379.

Bayesian Analysis of Mixed-effect Regression Models Driven by Ordinary Differential Equations

Tan, Q., & Ghosal, S. (2019, August 9). Sankhya B, Vol. 83, pp. 3–29.

Bayesian Inference in Nonparanormal Graphical Models

Mulgrave, J. J., & Ghosal, S. (2019, June 5). Bayesian Analysis, Vol. 15, pp. 449–475.

Bayesian modeling of the structural connectome for studying Alzheimer’s disease

Roy, A., Ghosal, S., Prescott, J., Choudhury, R., & Kingshuk. (2019, September 1). The Annals of Applied Statistics, Vol. 13, pp. 1791–1816.

Bayesian nonparametric estimation of ROC surface under verification bias

Zhu, R., & Ghosal, S. (2019, May 3). Statistics in Medicine.

Bayesian Discriminant Analysis Using a High Dimensional Predictor

Sankhya A, 80(S1), 112–145.

Bayesian Semiparametric ROC surface estimation under verification bias

Computational Statistics & Data Analysis, 133, 40–52.

Bayesian non-parametric simultaneous quantile regression for complete and grid data

Computational Statistics & Data Analysis, 127, 172–186.

Multivariate Gaussian network structure learning

Journal of Statistical Planning and Inference, 199, 327–342.

Analyzing ozone concentration by Bayesian spatio-temporal quantile regression

Environmetrics, 28(4), e2443.

Bayesian inference for higher-order ordinary differential equation models

Journal of Multivariate Analysis, 157, 103–114.

Fundamentals of Nonparametric Bayesian Inference

Ghosal, S., & Vaart, A. (2017, June 26). Cambridge University Press EBooks.

Median Analysis of Repeated Measures Associated with Recurrent Events in Presence of Terminal Event

Sundaram, R., Ma, L., & Ghoshal, S. (2017, April 28). The International Journal of Biostatistics, Vol. 13.

Posterior Contraction Rates of Density Derivative Estimation

Sankhya A, 79(2), 336–354.

Bayesian quantile regression using random B-spline series prior

Computational Statistics & Data Analysis, 109, 121–143.

Forward selection and estimation in high dimensional single index models

Statistical Methodology, 33, 172–179.

Supremum norm posterior contraction and credible sets for nonparametric multivariate regression

Yoo, W. W., & Ghosal, S. (2016, April 11). The Annals of Statistics, Vol. 44, pp. 1069–1102.

Adaptive Bayesian density regression for high-dimensional data

Shen, W., & Ghosal, S. (2015, September 30). Bernoulli, Vol. 22, pp. 396–420.

Bayesian estimation of sparse precision matrix.

Journal of Multivariate Analysis, 136, 147–162.

Bayesian structure learning in graphical models

Journal of Multivariate Analysis, 136, 147–162.

Prediction consistency of forward iterated regression and selection technique

Statistics & Probability Letters, 107, 79–83.

Sparse Penalized Forward Selection for Support Vector Classification

Journal of Computational and Graphical Statistics, 25(2), 493–514.

Special issue on Bayesian nonparametrics

Journal of Statistical Planning and Inference, 166, 1.

Bayesian ROC curve estimation under verification bias

Statistics in Medicine, 33(29), 5081–5096.

Bayesian variable selection in generalized additive partial linear models

Stat, 3(1), 363–378.

Multiple Testing Approaches for Removing Background Noise from Images

In Springer Proceedings in Mathematics & Statistics (pp. 95–104).

Denoising three-dimensional and colored images using a Bayesian multi-scale model for photon counts

Signal Processing, 93(11), 2906–2914.

Fast Bayesian model assessment for nonparametric additive regression

Computational Statistics & Data Analysis, 71, 347–358.

Iterative selection using orthogonal regression techniques

Statistical Analysis and Data Mining, 6(6), 557–564.

Finite skew-mixture models for estimation of positive false discovery rates

Statistical Methodology, 10(1), 46–57.

OPTIMAL TWO-STAGE PROCEDURES FOR ESTIMATING LOCATION AND SIZE OF THE MAXIMUM OF A MULTIVARIATE REGRESSION FUNCTION

Wiardi Beckman Foundation (Wiardi Beckman Foundation), Vol. 40, pp. 2850–2876.

The L1-consistency of Dirichlet mixtures in multivariate Bayesian density estimation

Journal of Multivariate Analysis, 101(10), 2411–2419.

Bayesian ROC curve estimation under binormality using a rank likelihood

Journal of Statistical Planning and Inference, 139(6), 2076–2083.

Bayesian bootstrap estimation of ROC curve

Statistics in Medicine, 27(26), 5407–5420.

Convergence properties of sequential Bayesian D-optimal designs

Journal of Statistical Planning and Inference, 139(2), 425–440.

Strong approximations for resample quantile processes and application to ROC methodology

Journal of Nonparametric Statistics, 20(3), 229–240.

A consistent nonparametric Bayesian procedure for estimating autoregressive conditional densities

Computational Statistics & Data Analysis, 51(9), 4424–4437.

Nonparametric binary regression using a Gaussian process prior

Statistical Methodology, 4(2), 227–243.

Posterior consistency of Dirichlet mixtures for estimating a transition density

Journal of Statistical Planning and Inference, 137(6), 1711–1726.

Convergence rates of posterior distributions

Ghosal, S., Ghosh, J. K., Vaart, & W, A. (2000, April 1). The Annals of Statistics, Vol. 28, pp. 500–531.