2 citations · 3 across the 4 of their papers we have counts for
Showing stat.MEShow all
3 papers · 1 filter
stat.ME2022
A Bayesian Survival Tree Partition Model Using Latent Gaussian Processes
Richard D. Payne, Nilabja Guha, Bani K. Mallick
Survival models are used to analyze time-to-event data in a variety of disciplines. Proportional hazard models provide interpretable parameter estimates, but proportional hazards a…
stat.ME2017
A Conditional Density Estimation Partition Model Using Logistic Gaussian Processes
Richard D. Payne, Nilabja Guha, Yu Ding +1
Conditional density estimation (density regression) estimates the distribution of a response variable y conditional on covariates x. Utilizing a partition model framework, a condit…
stat.ME2014★ 1 cited
Two-Stage Metropolis-Hastings for Tall Data
Richard D. Payne, Bani K. Mallick
This paper discusses the challenges presented by tall data problems associated with Bayesian classification (specifically binary classification) and the existing methods to handle…