2 papers
stat.ME2025
Estimating Shapley Effects in Big-Data Emulation and Regression Settings using Bayesian Additive Regression Trees
Akira Horiguchi, Matthew T. Pratola
Shapley effects are a particularly interpretable approach to assessing how a function depends on its various inputs. The existing literature contains various estimators for this cl…
stat.ME2024
A tree perspective on stick-breaking models in covariate-dependent mixtures
Akira Horiguchi, Cliburn Chan, Li Ma
Stick-breaking (SB) processes are often adopted in Bayesian mixture models for generating mixing weights. When covariates influence the sizes of clusters, SB mixtures are particula…