1 citations · 2 across the 5 of their papers we have counts for
5 papers
Bayesian palaeoclimate reconstruction from zero-inflated count-compositional pollen data: A case study of Lago Grande di Monticchio in southern Italy
André F. B. Menezes, Andrew C. Parnell, Brian Huntley +1
Bayesian palaeoclimate reconstruction from fossil pollen counts relies on a modern pollen-climate calibration data set to infer the pollen-climate relationships used to reconstruct…
Bayesian nonparametric models for zero-inflated count-compositional data using ensembles of regression trees
André F. B. Menezes, Andrew C. Parnell, Keefe Murphy
Count-compositional data arise in many different fields, including high-throughput sequencing experiments, ecological surveys, and palaeoclimate studies, where a common, important…
Finite mixture representations of zero-and--inflated distributions for count-compositional data
André F. B. Menezes, Andrew C. Parnell, Keefe Murphy
We provide novel probabilistic portrayals of two multivariate models designed to handle zero-inflation in count-compositional data. We develop a new unifying framework that represe…
Joint Models for Handling Non-Ignorable Missing Data using Bayesian Additive Regression Trees: Application to Leaf Photosynthetic Traits Data
Yong Chen Goh, Wuu Kuang Soh, Andrew C. Parnell +1
Dealing with missing data poses significant challenges in predictive analysis, often leading to biased conclusions when oversimplified assumptions about the missing data process ar…
Seemingly unrelated Bayesian additive regression trees for cost-effectiveness analyses in healthcare
Jonas Esser, Mateus Maia, Andrew C. Parnell +4
In recent years, theoretical results and simulation evidence have shown Bayesian additive regression trees to be a highly-effective method for nonparametric regression. Motivated b…