Subhashis Ghoshal

Works (40)

Updated: April 5th, 2024 10:03

2023 journal article

Posterior contraction and testing for multivariate isotonic regression

ELECTRONIC JOURNAL OF STATISTICS, 17(1), 798–822.

author keywords: Multivariate isotonic regression; contraction rate; Bayesian tests for multivariate monotonicity
Source: Web Of Science
Added: May 15, 2023

2022 article

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

Ghosal, S. (2022, September 14). JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 117, pp. 1171–1174.

UN Sustainable Development Goal Categories
Source: Web Of Science
Added: October 24, 2022

2022 journal article

Rates and coverage for monotone densities using projection-posterior

BERNOULLI, 28(2), 1093–1119.

author keywords: Monotone density; contraction rate; Bayesian test for monotonicity; credible interval; coverage
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: March 28, 2022

2022 journal article

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

BERNOULLI, 28(3), 1625–1647.

By: P. Bhaumik n, W. Shi n & S. Ghosal n

author keywords: Partial differential equation; generalized regression; two-step method; projection posterior; Bernstein-von Mises theorem; contiguity; B-splines; tensor products
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: May 23, 2022

2021 journal article

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

ELECTRONIC JOURNAL OF STATISTICS, 15(2), 4545–4579.

author keywords: High-dimensional inference; Gaussian graphical model; measurement error; posterior contraction rate; sparsity
TL;DR: This paper incorporates measurement error in the context of estimating a sparse, high-dimensional precision matrix for a Gaussian graphical model with data corrupted by Gaussian measurement error with unknown variance and establishes a general result which gives sufficient conditions under which the posterior contraction rates that hold in the no-measurement-error case carry over to the measurement- error case. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: February 28, 2022

2021 journal article

Unified Bayesian theory of sparse linear regression with nuisance parameters

ELECTRONIC JOURNAL OF STATISTICS, 15(1), 3040–3111.

author keywords: Bernstein-von Mises theorems; High-dimensional regression; Model selection consistency; Posterior contraction rates; Sparse priors
Source: Web Of Science
Added: June 28, 2021

2020 journal article

BAYESIAN INFERENCE ON MULTIVARIATE MEDIANS AND QUANTILES

STATISTICA SINICA, 32(1), 517–538.

author keywords: Affine equivariance; Bayesian bootstrap; Donsker class; Dirichlet process; empirical process; multivariate median
Source: Web Of Science
Added: January 18, 2022

2020 journal article

Bayesian linear regression for multivariate responses under group sparsity

BERNOULLI, 26(3), 2353–2382.

author keywords: Bayesian variable selection; covariance matrix; group sparsity; multivariate linear regression; posterior contraction rate; Renyi divergence; spike-and-slab prior
TL;DR: The posterior contraction rate is derived using the general theory by constructing a suitable test from the first principle using moment bounds for certain likelihood ratios, which leads to posterior concentration around the truth with respect to the average Renyi divergence of order 1/2. (via Semantic Scholar)
Source: Web Of Science
Added: May 18, 2020

2020 journal article

Posterior contraction and credible sets for filaments of regression functions

ELECTRONIC JOURNAL OF STATISTICS, 14(1), 1707–1743.

author keywords: Filament; nonparametric regression; posterior contraction; credibility; coverage; B-splines
Source: Web Of Science
Added: August 3, 2020

2020 journal article

Posterior contraction in sparse generalized linear models

BIOMETRIKA, 108(2), 367–379.

author keywords: Fractional posterior; Generalized linear model; High-dimensional regression; Posterior contraction rate; Sparsity-inducing prior
TL;DR: This work studies posterior contraction rates in sparse high-dimensional generalized linear models using priors incorporating sparsity, and shows that Bayesian methods achieve convergence properties analogous to lasso-type procedures. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: July 12, 2021

2018 journal article

Bayesian Discriminant Analysis Using a High Dimensional Predictor

Sankhya A, 80(S1), 112–145.

author keywords: Discriminant analysis; High dimensional predictor; Posterior concentration; Shrinkage prior; Sparsity
TL;DR: This work considers the problem of Bayesian discriminant analysis using a high dimensional predictor and obtains the contraction rate of the posterior distribution for the mean and the precision matrix respectively using the Euclidean and the Frobenius distance. (via Semantic Scholar)
UN Sustainable Development Goal Categories
10. Reduced Inequalities (OpenAlex)
Sources: Crossref, Web Of Science
Added: July 15, 2019

2018 journal article

Bayesian Semiparametric ROC surface estimation under verification bias

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

By: R. Zhu n & S. Ghosal n

author keywords: ROC surface; Verification bias correction; Trinormal model; MAR assumption
TL;DR: A Bayesian approach for estimating the ROC surface is proposed based on continuous data under a semi-parametric trinormality assumption and is applied to evaluate the performance of CA125 and HE4 in the diagnosis of epithelial ovarian cancer (EOC) as a demonstration. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Crossref, Web Of Science
Added: March 25, 2019

2018 journal article

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

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

author keywords: B-spline prior; Black-box optimization; Block Metropolis-Hastings; Non-parametric quantile regression; North Atlantic hurricane data; US household income data
Source: Crossref
Added: January 19, 2020

2018 journal article

Multivariate Gaussian network structure learning

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

author keywords: Graphical model; Group penalty; Multivariate normal; Rate of convergence
TL;DR: This work considers a graphical model where a multivariate normal vector is associated with each node of the underlying graph and estimates the graphical structure and shows the superiority of the proposed method over comparable procedures. (via Semantic Scholar)
Sources: Crossref, Web Of Science
Added: November 5, 2018

2017 journal article

Analyzing ozone concentration by Bayesian spatio-temporal quantile regression

Environmetrics, 28(4), e2443.

author keywords: B-spline prior; block Metropolis-Hastings; spatio-temporal quantile regression; U; S; ozone data
Source: Crossref
Added: January 19, 2020

2017 journal article

Bayesian inference for higher-order ordinary differential equation models

Journal of Multivariate Analysis, 157, 103–114.

By: P. Bhaumik & S. Ghosal n

author keywords: Bayesian inference; Bernstein-von Mises theorem; Higher order ordinary differential equation; Runge-Kutta method; Spline smoothing
TL;DR: Bernstein-von Mises theorems are established for the posterior distribution of the parameter vector for each method with $n^{-1/2}$ contraction rate and they are applied to the higher order ODE model. (via Semantic Scholar)
Source: Crossref
Added: January 19, 2020

2017 journal article

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

INTERNATIONAL JOURNAL OF BIOSTATISTICS, 13(1).

By: R. Sundaram*, L. Ma* & S. Ghoshal n

author keywords: recurrent events; quantile regression; informative censoring; estimating equations; survival analysis
MeSH headings : Computer Simulation; Female; Follow-Up Studies; Humans; Models, Statistical; Ovarian Neoplasms / economics; Ovarian Neoplasms / therapy; Recurrence; Research Design
TL;DR: A semiparametric model for assessing the effect of covariates on the quantiles of the point processes is proposed and both the finite sample as well as the large sample properties of the proposed estimators are investigated. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2017 journal article

Posterior Contraction Rates of Density Derivative Estimation

Sankhya A, 79(2), 336–354.

author keywords: B-spline; Density derivative estimation; Nonparametric Bayes; Posterior contraction rate; Tensor product
UN Sustainable Development Goal Categories
Source: Crossref
Added: January 19, 2020

2016 journal article

Bayesian quantile regression using random B-spline series prior

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

author keywords: B-spline prior; Gaussian process; Quantile regression; Atlantic Hurricane data; US population data
TL;DR: The proposed Bayesian method is extended to multidimensional predictors such that the quantile regression depends on the predictors through an unknown linear combination only. (via Semantic Scholar)
Source: Crossref
Added: January 19, 2020

2016 journal article

Forward selection and estimation in high dimensional single index models

Statistical Methodology, 33, 172–179.

By: S. Luo n & S. Ghosal n

author keywords: Forward selection; High dimension; Sparsity; Single index model; Penalization; Variable selection
TL;DR: A new penalized forward selection technique which can reduce highdimensional optimization problems to several one dimensional optimization problems by choosing the best predictor and then iterating the selection steps until convergence is proposed. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Crossref, Web Of Science
Added: August 6, 2018

2015 journal article

Bayesian structure learning in graphical models

Journal of Multivariate Analysis, 136, 147–162.

author keywords: Graphical lasso; Graphical models; Laplace approximation; Posterior convergence; Precision matrix
TL;DR: This paper considers the problem of estimating a sparse precision matrix of a multivariate Gaussian distribution, where the dimension p may be large, and proposes a fast computational method for approximating the posterior probabilities of various graphs using the Laplace approximation approach. (via Semantic Scholar)
Source: Crossref
Added: January 19, 2020

2015 journal article

Prediction consistency of forward iterated regression and selection technique

Statistics & Probability Letters, 107, 79–83.

By: S. Luo n & S. Ghosal n

author keywords: Forward selection; High dimension; Sparsity; Linear regression; Penalization; Prediction consistency
Sources: Crossref, Web Of Science
Added: August 6, 2018

2015 journal article

Sparse Penalized Forward Selection for Support Vector Classification

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

By: S. Ghosal, B. Turnbull, H. Zhang & W. Hwang

author keywords: High dimension; Penalization; Sparsity; SVM; Variable selection
TL;DR: Comparison of the proposed new classification rule with ℓ1-SVM and other common methods show very promising performance, in that the proposed method leads to much leaner models without compromising misclassification rates, particularly for high-dimensional predictors. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Source: Crossref
Added: January 19, 2020

2015 journal article

Special issue on Bayesian nonparametrics

Journal of Statistical Planning and Inference, 166, 1.

By: S. Ghoshal n, B. Kleijn*, A. van der Vaart* & H. van Zanten*

Source: Crossref
Added: January 19, 2020

2014 journal article

Bayesian ROC curve estimation under verification bias

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

author keywords: binormal model; MAR assumption; posterior consistency; ROC curve; verification bias-correction
MeSH headings : Bayes Theorem; Bias; Computer Simulation; Data Interpretation, Statistical; Humans; Markov Chains; Models, Biological; Monte Carlo Method; Patient Selection; ROC Curve; Regression Analysis
TL;DR: A new Bayesian approach for estimating an ROC curve based on continuous data following the popular semiparametric binormal model in the presence of verification bias is proposed and it is concluded that the estimator performs well in terms of accuracy. (via Semantic Scholar)
Source: Crossref
Added: April 10, 2022

2014 journal article

Bayesian variable selection in generalized additive partial linear models

Stat, 3(1), 363–378.

author keywords: generalized additive models; group lasso; Laplace approximation; penalized regression; variable selection
UN Sustainable Development Goal Categories
Source: Crossref
Added: April 10, 2022

2014 chapter

Multiple Testing Approaches for Removing Background Noise from Images

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

By: J. White* & S. Ghosal n

TL;DR: This article formalizes the choice of thresholding through a multiple testing approach and employs a Gaussian mixture to estimate the unknown common null value of the background intensity level in noisy X-ray images of a supernova remnant. (via Semantic Scholar)
Source: Crossref
Added: April 10, 2022

2013 journal article

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

Signal Processing, 93(11), 2906–2914.

By: J. Thomas White* & S. Ghosal n

TL;DR: The proposed method is completely data-driven, since all smoothing parameters are automatically estimated from the data without any additional user input, and can be used to process medical images as well. (via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Source: Crossref
Added: April 10, 2022

2013 journal article

Fast Bayesian model assessment for nonparametric additive regression

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

By: S. McKay Curtis n, S. Banerjee n & S. Ghosal n

author keywords: Group LASSO; Laplace approximation; Model uncertainty; Penalized regression; Variable selection
Sources: Crossref, Web Of Science
Added: August 6, 2018

2013 journal article

Iterative selection using orthogonal regression techniques

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

By: B. Turnbull n, S. Ghosal n & H. Zhang*

author keywords: forward selection; orthogonalization; high dimensional regression; LASSO
TL;DR: The new strategy, called the Selection Technique in Orthogonalized Regression Models (STORM), turns out to be extremely successful in reducing the model dimension further and also leads to improved predicting power. (via Semantic Scholar)
Source: Crossref
Added: April 10, 2022

2012 journal article

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

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

By: G. Bean*, E. Dimarco*, L. Mercer*, L. Thayer*, A. Roy* & S. Ghosal n

author keywords: Multiple testing; p-value density; Shape restriction
UN Sustainable Development Goal Categories
Source: Crossref
Added: April 10, 2022

2012 journal article

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

ANNALS OF STATISTICS, 40(6), 2850–2876.

By: E. Belitser n, S. Ghosal n & H. Zanten n

author keywords: Two-stage procedure; optimal rate; sequential design; multi-stage procedure; adaptive estimation
Source: Web Of Science
Added: March 22, 2021

2010 journal article

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

By: Y. Wu* & S. Ghosal n

author keywords: Posterior consistency; Dirichlet process; Mixture; Posterior consistency; Posterior distribution; Kullback-Leibler property; Multivariate; Density estimation
TL;DR: The L"1-consistency of Dirichlet mixutures in the multivariate density estimation setting is extended and the Kullback-Leibler property of the prior holds and the size of the sieve in the parameter space in terms of L" 1-metric entropy is not larger than the order of n. (via Semantic Scholar)
Source: Crossref
Added: April 10, 2022

2008 journal article

Bayesian ROC curve estimation under binormality using a rank likelihood

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

By: J. Gu* & S. Ghosal n

author keywords: Binormal model; MCMC; Rank-based likelihood; ROC curve; Posterior consistency
TL;DR: This paper proposes a conceptually simple and computationally feasible Bayesian estimation method using a rank-based likelihood and concludes that the estimator generally performs better than its competitors. (via Semantic Scholar)
UN Sustainable Development Goal Categories
5. Gender Equality (Web of Science)
Source: Crossref
Added: April 10, 2022

2008 journal article

Bayesian bootstrap estimation of ROC curve

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

By: J. Gu*, S. Ghosal n & A. Roy*

author keywords: area under the curve (AUC); Bayesian bootstrap; integrated absolute error; ROC Curve; testing binormality
MeSH headings : Bayes Theorem; Computer Simulation; Data Interpretation, Statistical; Diagnostic Tests, Routine / methods; Humans; Models, Statistical; Predictive Value of Tests; Prognosis; ROC Curve; Research Design; Software; Statistics, Nonparametric
UN Sustainable Development Goal Categories
5. Gender Equality (Web of Science)
10. Reduced Inequalities (OpenAlex)
Sources: Crossref, Web Of Science
Added: August 6, 2018

2008 journal article

Convergence properties of sequential Bayesian D-optimal designs

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

author keywords: Adaptive designs; Asymptotic normality; Discrete optimal design; Dose-response; Posterior convergence
TL;DR: For sequential D-optimality under a general nonlinear location-scale model for binary experiments, posterior consistency, consistency of the design measure, and the asymptotic normality of posterior following the design are established. (via Semantic Scholar)
Sources: Crossref, Web Of Science
Added: August 6, 2018

2008 journal article

Strong approximations for resample quantile processes and application to ROC methodology

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

By: J. Gu* & S. Ghosal n

author keywords: Bayesian bootstrap; Kiefer process; ROC curve; strong approximation; quantile process
Sources: Crossref, Web Of Science
Added: August 6, 2018

2006 journal article

A consistent nonparametric Bayesian procedure for estimating autoregressive conditional densities

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

author keywords: Dirichlet process mixture models; posterior consistency; no-gaps algorithm
TL;DR: A Bayesian infinite mixture model for the estimation of the conditional density of an ergodic time series that can approximate any linear autoregressive model arbitrarily closely while imposing no constraint on parameters to ensure stationarity is proposed. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Crossref, Web Of Science
Added: August 6, 2018

2006 journal article

Nonparametric binary regression using a Gaussian process prior

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

By: N. Choudhuri, S. Ghosal n & A. Roy*

Source: Crossref
Added: April 10, 2022

2006 journal article

Posterior consistency of Dirichlet mixtures for estimating a transition density

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

By: Y. Tang* & S. Ghosal n

author keywords: Dirichlet mixture; Markov process; posterior consistency; transition density; uniformly exponentially consistent tests
UN Sustainable Development Goal Categories
Sources: Crossref, Web Of Science
Added: August 6, 2018

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