Comparing Bayesian Spatial Conditional Overdispersion and the Besag–York–Mollié Models: Application to Infant Mortality Rates

Comparing Bayesian Spatial Conditional Overdispersion and the Besag–York–Mollié Models: Application to Infant Mortality Rates

In this paper, we review overdispersed Bayesian generalized spatial conditional count data models. Their usefulness is illustrated with their application to infant mortality rates from Colombian regions and by comparing them with the widely used Besag–York–Mollié (BYM) models. These overdispersed mo...

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Bibliographic Details
Main Authors: Mabel Morales-Otero, Vicente Núñez-Antón
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Mathematics
Subjects:
Bayesian models
count data
infant mortality rates
INLA
MCMC
spatial statistics
Online Access:https://www.mdpi.com/2227-7390/9/3/282

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