Hierarchical Bayes estimation of spatial statistics for rates

DOI10.1016/j.jspi.2011.07.026zbMath1232.62050OpenAlexW2080507889MaRDI QIDQ643414

Mahmoud Torabi

Publication date: 28 October 2011

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2011.07.026

zbMATH Keywords

time serieshierarchical Bayesgeographical variationmodel adequacymixed effect model

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15) Monte Carlo methods (65C05)

Related Items (12)

Likelihood inference for small area estimation using data cloning ⋮ Estimation of Crop Yields and Insurance Premiums Using a Shrinkage Estimator ⋮ Likelihood Inference for Spatial Generalized Linear Mixed Models ⋮ Zero‐inflated spatio‐temporal models for disease mapping ⋮ Spatio–temporal modeling for disease mapping using CAR and B‐spline smoothing ⋮ Spatiotemporal modeling of odds of disease ⋮ Likelihood inference in small area estimation by combining time-series and cross-sectional data ⋮ Spatial modeling using frequentist approach for disease mapping ⋮ Hierarchical Bayesian bivariate disease mapping: analysis of children and adults asthma visits to hospital ⋮ Small Area Estimation via Multivariate Fay-Herriot Models with Latent Spatial Dependence ⋮ Hierarchical Bayes estimation in small area estimation using cross-sectional and time-series data ⋮ Hierarchical multivariate mixture generalized linear models for the analysis of spatial data: An application to disease mapping

Uses Software

• R
• WinBUGS
• boa

Cites Work

• Bayesian image restoration, with two applications in spatial statistics (with discussion)
• Inference from iterative simulation using multiple sequences
• Autoregressive Spatial Smoothing and Temporal Spline Smoothing for Mapping Rates
• Small area estimation using unmatched sampling and linking models
• A Hierarchical Model for Space–Time Surveillance Data on Meningococcal Disease Incidence
• Sampling-Based Approaches to Calculating Marginal Densities
• Bayesian Measures of Model Complexity and Fit
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