Bayesian spatiotemporal analysis of zero-inflated biological population density data by a delta-normal spatiotemporal additive model

DOI10.1002/bimj.201400123zbMath1381.62269OpenAlexW2139802596WikidataQ30999055 ScholiaQ30999055MaRDI QIDQ2802566

Nunziata Ribecco, Simona Arcuti, Alessio Pollice, Gianfranco D'Onghia

Publication date: 26 April 2016

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/bimj.201400123

zbMATH Keywords

Bayesian analysisMCMCzero-inflated datageneralized additive modelsbiological population dynamics

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Population dynamics (general) (92D25)

Uses Software

• R
• CODA
• WinBUGS
• SemiPar
• rjags
• JAGS
• R2jags

Cites Work

• Unnamed Item
• A Bayesian analysis for longitudinal semicontinuous data with an application to an acupuncture clinical trial
• Mixed effects models and extensions in ecology with R
• A weakly informative default prior distribution for logistic and other regression models
• Small area estimation for semicontinuous skewed spatial data: An application to the grape wine production in Tuscany
• Bivariate Binomial Spatial Modeling of Loa loa Prevalence in Tropical Africa
• Finding Groups in Data
• A Two-Part Random-Effects Model for Semicontinuous Longitudinal Data
• Semiparametric Regression
• Adaptive Rejection Sampling for Gibbs Sampling
• Structured Additive Regression for Categorical Space–Time Data: A Mixed Model Approach
• Modelling Longitudinal Semicontinuous Emesis Volume Data with Serial Correlation in an Acupuncture Clinical Trial
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

This page was built for publication: Bayesian spatiotemporal analysis of zero-inflated biological population density data by a delta-normal spatiotemporal additive model