CARBayes: An R Package for Spatial Areal Unit Modelling with Conditional Autoregressive Priors
نویسنده
چکیده
This is a vignette for the R package CARBayes version 4.1, and is an updated version of a paper in the Journal of Statistical Software in 2013 Volume 55 Issue 13 by the same author. This vignette describes the class of models that can be implemented in CARBayes, and gives 3 worked examples of spatial data analysis using the package.
منابع مشابه
CARBayes: An R Package for Bayesian Spatial Modelling with Conditional Autoregressive Priors
This is a vignette for the R package CARBayes version 4, and is an updated version of a paper in the Journal of Statistical Software in 2013 Volume 55 Issue 13 with the same title and author. This vignette is required because CARBayes has been updated both in terms of syntax and functionality since the paper appeared in the Journal of Statistical Software.
متن کاملFully Bayesian spline smoothing and intrinsic autoregressive priors By PAUL
There is a well-known Bayesian interpretation for function estimation by spline smoothing using a limit of proper normal priors. The limiting prior and the conditional and intrinsic autoregressive priors popular for spatial modelling have a common form, which we call partially informative normal. We derive necessary and sufficient conditions for the propriety of the posterior for this class of ...
متن کاملBayesian cluster detection via adjacency modelling.
Disease mapping aims to estimate the spatial pattern in disease risk across an area, identifying units which have elevated disease risk. Existing methods use Bayesian hierarchical models with spatially smooth conditional autoregressive priors to estimate risk, but these methods are unable to identify the geographical extent of spatially contiguous high-risk clusters of areal units. Our proposed...
متن کاملBayesian modelling strategies for spatially varying regression coefficients: A multivariate perspective for multiple outcomes
This paper considers modelling spatially varying regression effects for multivariate mortality count outcomes. Alternative approaches to spatial regression heterogeneity are considered: the multivariate normal conditional autoregressive (MCAR) model is contrasted with a flexible set of priors based on the multiple membership approach. These include spatial factor priors and a nonparametric appr...
متن کاملOn a Class of Shrinkage Priors for Covariance Matrix Estimation
We propose a flexible class of models based on scale mixture of uniform distributions to construct shrinkage priors for covariance matrix estimation. This new class of priors enjoys a number of advantages over the traditional scale mixture of normal priors, including its simplicity and flexibility in characterizing the prior density. We also exhibit a simple, easy to implement Gibbs sampler for...
متن کامل