88 citations · 268 across the 30 of their papers we have counts for
32 papers
Multivariate Varying-Coefficient BART with Graphical Horseshoe Priors
Soham Ghosh, Sameer K. Deshpande
Modern multivariate regression problems involve several related outcomes whose regression effects are not only nonlinear, heterogeneous, and outcome-specific, but also where the re…
Quantifying the limits of human athletic performance: A Bayesian analysis of elite decathletes
Paul-Hieu V. Nguyen, James M. Smoliga, Benton Lindaman +1
Because the decathlon tests many facets of athleticism, including sprinting, throwing, jumping, and endurance, many consider it to be the ultimate test of athletic ability. On this…
Fitting sparse high-dimensional varying-coefficient models with Bayesian regression tree ensembles
Soham Ghosh, Saloni Bhogale, Sameer K. Deshpande
By allowing the effects of covariates in a linear regression model to vary as functions of additional effect modifiers, varying-coefficient models (VCMs) strike a compellin…
High-dimensional regression with outcomes of mixed-type using the multivariate spike-and-slab LASSO
Soham Ghosh, Sameer K. Deshpande
We consider a high-dimensional multi-outcome regression in which possibly dependent, binary and continuous outcomes are regressed onto covariates. We model the observed ou…
Oblique Bayesian additive regression trees
Paul-Hieu V. Nguyen, Ryan Yee, Sameer K. Deshpande
Current implementations of Bayesian Additive Regression Trees (BART) are based on axis-aligned decision rules that recursively partition the feature space using a single feature at…
Scalable piecewise smoothing with BART
Ryan Yee, Soham Ghosh, Sameer K. Deshpande
Although it is an extremely effective, easy-to-use, and increasingly popular tool for nonparametric regression, the Bayesian Additive Regression Trees (BART) model is limited by th…
Moving from Machine Learning to Statistics: the case of Expected Points in American football
Ryan S. Brill, Ryan Yee, Sameer K. Deshpande +1
Expected points is a value function fundamental to player evaluation and strategic in-game decision-making across sports analytics, particularly in American football. To estimate e…
Heterogeneous Treatment Effect Estimation under Noncompliance in the Illinois Workplace Wellness Study with Bayesian Tree Ensembles
Jared D. Fisher, David W. Puelz, Sameer K. Deshpande
Estimating varying treatment effects in randomized trials with noncompliance is inherently challenging since variation comes from two separate sources: variation in the impact itse…
Adolescent sports participation and health in early adulthood: An observational study
Ajinkya H. Kokandakar, Yuzhou Lin, Steven Jin +5
We study the impact of teenage sports participation on early-adulthood health using longitudinal data from the National Study of Youth and Religion. We focus on two primary outcome…
New directions in algebraic statistics: Three challenges from 2023
Yulia Alexandr, Miles Bakenhus, Mark Curiel +11
In the last quarter of a century, algebraic statistics has established itself as an expanding field which uses multilinear algebra, commutative algebra, computational algebra, geom…
Evaluating plate discipline in Major League Baseball with Bayesian Additive Regression Trees
Ryan Yee, Sameer K. Deshpande
We introduce a three-step framework to determine at which pitches Major League batters should swing. Unlike traditional plate discipline metrics, which implicitly assume that all b…
Are you using test log-likelihood correctly?
Sameer K. Deshpande, Soumya Ghosh, Tin D. Nguyen +1
Test log-likelihood is commonly used to compare different models of the same data or different approximate inference algorithms for fitting the same probabilistic model. We present…
flexBART: Flexible Bayesian regression trees with categorical predictors
Sameer K. Deshpande
Most implementations of Bayesian additive regression trees (BART) one-hot encode categorical predictors, replacing each one with several binary indicators, one for every level or c…
Pre-analysis protocol for an observational study on the effects of adolescent sports participation on health in early adulthood
Ajinkya H Kokandakar, Yuzhou Lin, Steven Jin +5
We will study the impact of adolescent sports participation on early-adulthood health using longitudinal data from the National Study of Youth and Religion. We focus on two primary…
Bayesian Causal Forests & the 2022 ACIC Data Challenge: Scalability and Sensitivity
Ajinkya H. Kokandakar, Hyunseung Kang, Sameer K. Deshpande
We demonstrate how Hahn et al.'s Bayesian Causal Forests model (BCF) can be used to estimate conditional average treatment effects for the longitudinal dataset in the 2022 American…
A Bayesian analysis of the time through the order penalty in baseball
Ryan S. Brill, Sameer K. Deshpande, Abraham J. Wyner
As a baseball game progresses, batters appear to perform better the more times they face a particular pitcher. The apparent drop-off in pitcher performance from one time through th…
Posterior contraction and uncertainty quantification for the multivariate spike-and-slab LASSO
Yunyi Shen, Sameer K. Deshpande
We study the asymptotic properties of Deshpande et al.\ (2019)'s multivariate spike-and-slab LASSO (mSSL) procedure for simultaneous variable and covariance selection in the sparse…
Estimating sparse direct effects in multivariate regression with the spike-and-slab LASSO
Yunyi Shen, Claudia Solís-Lemus, Sameer K. Deshpande
The multivariate regression interpretation of the Gaussian chain graph model simultaneously parametrizes (i) the direct effects of predictors on outcomes and (ii) the resid…
Measuring the robustness of Gaussian processes to kernel choice
William T. Stephenson, Soumya Ghosh, Tin D. Nguyen +3
Gaussian processes (GPs) are used to make medical and scientific decisions, including in cardiac care and monitoring of atmospheric carbon dioxide levels. Notably, the choice of GP…
Confidently Comparing Estimators with the c-value
Brian L. Trippe, Sameer K. Deshpande, Tamara Broderick
Modern statistics provides an ever-expanding toolkit for estimating unknown parameters. Consequently, applied statisticians frequently face a difficult decision: retain a parameter…
Approximate Cross-Validation for Structured Models
Soumya Ghosh, William T. Stephenson, Tin D. Nguyen +2
Many modern data analyses benefit from explicitly modeling dependence structure in data -- such as measurements across time or space, ordered words in a sentence, or genes in a gen…
VCBART: Bayesian trees for varying coefficients
Sameer K. Deshpande, Ray Bai, Cecilia Balocchi +2
The linear varying coefficient models posits a linear relationship between an outcome and covariates in which the covariate effects are modeled as functions of additional effect mo…
Crime in Philadelphia: Bayesian Clustering with Particle Optimization
Cecilia Balocchi, Sameer K. Deshpande, Edward I. George +1
Accurate estimation of the change in crime over time is a critical first step towards better understanding of public safety in large urban environments. Bayesian hierarchical model…
Expected Hypothetical Completion Probability
Sameer K. Deshpande, Katherine Evans
Using high-resolution player tracking data made available by the National Football League (NFL) for their 2019 Big Data Bowl competition, we introduce the Expected Hypothetical Com…