CARrampsOcl: Reparameterized and marginalized posterior sampling for conditional autoregressive models, OpenCL implementation

This package fits Bayesian conditional autoregressive models for spatial and spatiotemporal data on a lattice. It uses OpenCL kernels running on GPUs to perform rejection sampling to obtain independent samples from the joint posterior distribution of model parameters.

Package details

AuthorKate Cowles and Michael Seedorff and Alex Sawyer
MaintainerKate Cowles <>
LicenseGPL (>= 3)
Package repositoryView on CRAN
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CARrampsOcl documentation built on May 2, 2019, 3:27 a.m.