25 citations · 27 across the 7 of their papers we have counts for
9 papers
Bayesian index models for heterogeneous treatment effects
Hyung Park, Danni Wu, Eva Petkova +2
The general idea of this article is to develop a Bayesian model with a flexible link function connecting an exponential family treatment response to a linear combination of covaria…
Unsupervised Bayesian classification for models with scalar and functional covariates
Nancy L. Garcia, Mariana Rodrigues-Motta, Helio S. Migon +5
We consider unsupervised classification by means of a latent multinomial variable which categorizes a scalar response into one of L components of a mixture model. This process can…
Bivariate Hierarchical Bayesian Model for Combining Summary Measures and their Uncertainties from Multiple Sources
Yujing Yao, R. Todd Ogden, Chubing Zeng +1
It is often of interest to combine available estimates of a similar quantity from multiple data sources. When the corresponding variances of each estimate are also available, a mod…
Simultaneous Confidence Corridors for Mean Functions in Functional Data Analysis of Imaging Data
Yueying Wang, Guannan Wang, Li Wang +1
Motivated by recent work involving the analysis of biomedical imaging data, we present a novel procedure for constructing simultaneous confidence corridors for the mean of imaging…
A single-index model with a surface-link for optimizing individualized dose rules
Hyung Park, Eva Petkova, Thaddeus Tarpey +1
This paper focuses on the problem of modeling and estimating interaction effects between covariates and a continuous treatment variable on an outcome, using a single-index regressi…
Functional additive models for optimizing individualized treatment rules
Hyung Park, Eva Petkova, Thaddeus Tarpey +1
A novel functional additive model is proposed which is uniquely modified and constrained to model nonlinear interactions between a treatment indicator and a potentially large numbe…
A constrained sparse additive model for treatment effect-modifier selection
Hyung Park, Eva Petkova, Thaddeus Tarpey +1
Sparse additive modeling is a class of effective methods for performing high-dimensional nonparametric regression. This paper develops a sparse additive model focused on estimation…
Sufficient Dimension Reduction for Interactions
Hyung Park, Eva Petkova, Thaddeus Tarpey +1
Dimension reduction lies at the heart of many statistical methods. In regression, dimension reduction has been linked to the notion of sufficiency whereby the relation of the respo…
Wavelet-Based Scalar-on-Function Finite Mixture Regression Models
Adam Ciarleglio, R. Todd Ogden
Classical finite mixture regression is useful for modeling the relationship between scalar predictors and scalar responses arising from subpopulations defined by the differing asso…