P
Pulak Ghosh
Researcher at Indian Institute of Management Ahmedabad
Publications - 103
Citations - 2024
Pulak Ghosh is an academic researcher from Indian Institute of Management Ahmedabad. The author has contributed to research in topics: Random effects model & Dirichlet process. The author has an hindex of 23, co-authored 92 publications receiving 1763 citations. Previous affiliations of Pulak Ghosh include Indian Institute of Management Bangalore & University of Rochester.
Papers
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Journal ArticleDOI
A Bayesian semiparametric multivariate joint model for multiple longitudinal outcomes and a time-to-event.
Dimitris Rizopoulos,Pulak Ghosh +1 more
TL;DR: A new semiparametric multivariate joint model is proposed that relates multiple longitudinal outcomes to a time-to-event and key components of the model are modelled nonparametrically to allow for greater flexibility.
Proceedings Article
Likelihood based inference for skew-normal independent linear mixed models
TL;DR: In this article, a new class of asym- metric linear mixed models that provides for an efficient estimation of the parame- ters in the analysis of longitudinal data is presented. But the accuracy of the assumed normal distribu- tion is crucial for valid inference of the parameters.
Journal ArticleDOI
Robust mixture modeling based on scale mixtures of skew-normal distributions
TL;DR: Some simulation studies are presented to show the advantage of this flexible class of probability distributions in clustering heterogeneous data and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties.
Journal ArticleDOI
Posterior Consistency of Bayesian Quantile Regression Based on the Misspecified Asymmetric Laplace Density
TL;DR: An asymptotic justication for the widely used and em- pirically veried approach of assuming an asymmetric Laplace distribution for the response in Bayesian Quantile Regression by establishing posterior consistency and deriving the rate of convergence under the ALD misspecication.
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A Spatial Poisson Hurdle Model for Exploring Geographic Variation in Emergency Department Visits
TL;DR: A spatial Poisson hurdle model to explore geographic variation in emergency department (ED) visits while accounting for zero inflation is developed and it is shown that modeling the between-component correlation reduces bias in parameter estimates.