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Bayesian regression with spatiotemporal varying coefficients
Author(s) -
NietoBarajas Luis E.
Publication year - 2020
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201900098
Subject(s) - multivariate statistics , bayesian probability , independent and identically distributed random variables , context (archaeology) , bayesian linear regression , statistics , bayesian multivariate linear regression , regression , mathematics , econometrics , marginal distribution , joint probability distribution , linear regression , computer science , bayesian inference , geography , random variable , archaeology
To study the impact of climate variables on morbidity of some diseases in Mexico, we propose a spatiotemporal varying coefficients regression model. For that we introduce a new spatiotemporal‐dependent process prior, in a Bayesian context, with identically distributed normal marginal distributions and joint multivariate normal distribution. We study its properties and characterise the dependence induced. Our results show that the effect of climate variables, on the incidence of specific diseases, is not constant across space and time and our proposed model is able to capture and quantify those changes.