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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.
Getting started
Browse package contents
Package details |
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| Author | Kate Cowles and Michael Seedorff and Alex Sawyer |
| Maintainer | Kate Cowles <kate-cowles@uiowa.edu> |
| License | GPL (>= 3) |
| Version | 0.1.4 |
| Package repository | View on CRAN |
| Installation |
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