Modeling Disease Incidence Data with Spatial and Spatio Temporal Dirichlet Process Mixtures
From MaRDI portal
Publication:5123001
DOI10.1002/bimj.200610375zbMath1442.62456OpenAlexW2168820521WikidataQ31132677 ScholiaQ31132677MaRDI QIDQ5123001
Alan E. Gelfand, Athanasios Kottas, Jason A. Duan
Publication date: 25 September 2020
Published in: Biometrical Journal (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/bimj.200610375
Gaussian processesdisease mappingDirichlet process mixture modelsareal unit spatial datadynamic spatial process models
Related Items (8)
An area-specific stick breaking process for spatial data ⋮ Discussion of paper ``Nonparametric Bayesian inference in applications by Peter Müller, Fernando A. Quintana and Garritt L. Page ⋮ Spatial correlated incidence modeling with zero inflation ⋮ Bayesian non-parametric modeling for integro-difference equations ⋮ Spatio-temporal modeling of sudden infant death syndrome data ⋮ Process modelling for contingency tables with ordered categories ⋮ Mitigating unobserved spatial confounding when estimating the effect of supermarket access on cardiovascular disease deaths ⋮ Disease Mapping With Generative Models
This page was built for publication: Modeling Disease Incidence Data with Spatial and Spatio Temporal Dirichlet Process Mixtures
