spBayes: Univariate and Multivariate Spatio-temporal Modeling
spBayes fits univariate and multivariate models with Markov chain Monte Carlo (MCMC). Core functions include:
- spLM – univariate Gaussian regression with spatial random effects
- spMvLM – multivariate Gaussian regression with spatial random effects
- spGLM – univariate Logistic and Poisson regression with spatial random effects
- spMvGLM – multivariate Logistic and Poisson regression with spatial random effects
- spDynLM – univariate Gaussian regression with dynamic space-time random effects
For the core functions, a predictive process model can be specified for large data sets. Also adaptive MCMC is available for those parameters that cannot be updated using Gibbs. Course material and illustrations can be found here.
The stable version is available on CRAN.
The development version is available below.
|Depends:||R (≥ 1.8.0), coda, magic, abind, Formula|
|License:||GPL (≥ 2)|
|In views:||Bayesian, Spatial|
MBA: Multilevel B-spline Approximation
MBA generates surfaces interpolated from scattered data using Multilevel B-Splines. The most recent version is available on CRAN.