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spBayes (version 0.1-3)
Univariate and Multivariate Spatial Modeling
Description
spBayes fits univariate and multivariate models with Markov chain Monte Carlo (MCMC).
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Install
install.packages('spBayes')
Monthly Downloads
822
Version
0.1-3
License
GPL (>= 2)
Maintainer
Andrew Finley
Last Published
June 23rd, 2009
Functions in spBayes (0.1-3)
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Zurich.dat
Zurichberg Forest inventory data
BEF.dat
Bartlett Experimental Forest inventory data
FBC07.dat
Synthetic multivariate data with spatial and non-spatial variance structures
covInvLogDet
Utility function for constructing predictive process covariance matrices
iDist
Euclidean distance matrix
mkMvX
Make a multivariate design matrix
spGLM
Function for fitting univariate Bayesian generalized linear spatial regression models
pointsInPoly
Finds points in a polygon
hexGrid
Generates a hexagon tessellation within a bounding box
prior
Creates prior distribution definitions
spDIC
Calculates model DIC and associated statistics given a bayesLMRef, bayesLMConjugate, spGGT, spLM, spMvLM, bayesGeostatExact object
bayesLMRef
Simple Bayesian linear model with non-informative priors
spMvLM
Function for fitting multivariate Bayesian spatial regression models
adaptMetropGibbs
Adaptive Metropolis within Gibbs algorithm
spLM
Function for fitting univariate Bayesian spatial regression models
spPredict
Prediction for new points given a spGGT, spLM, spMvLM, spGLM, spMvGLM, or bayesGeostatExact object
WEF.dat
Western Experimental Forest inventory data
spGGT
Function for fitting univariate and multivariate Bayesian spatial regression models
spMvGLM
Function for fitting multivariate Bayesian generalized linear spatial regression models
synthetic.dat
Synthetic univariate data used for illustrations
FORMGMT.dat
Data used for illustrations
covGivens
Returns covariance matrix C given components of P and L in C=PLP'
bayesLMConjugate
Simple Bayesian linear model via the Normal/inverse-Gamma conjugate
bayesGeostatExact
Simple Bayesian spatial linear model with fixed semivariogram parameters
mvCovInvLogDet
Utility function for constructing multivariate predictive process covariance matrices