Bayesian Geostatistics Using Predictive Stacking


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Documentation for package ‘spStack’ version 1.1.1

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spStack-package spStack: Bayesian Geostatistics Using Predictive Stacking
candidateModels Create a collection of candidate models for stacking
cholUpdate Different Cholesky factor updates
cholUpdateDel Different Cholesky factor updates
cholUpdateDelBlock Different Cholesky factor updates
cholUpdateRankOne Different Cholesky factor updates
get_stacking_weights Optimal stacking weights
iDist Calculate distance matrix
posteriorPredict Prediction of latent process at new spatial or temporal locations
recoverGLMscale Recover posterior samples of scale parameters of spatial/spatial-temporal generalized linear models
simBinary Synthetic point-referenced binary data
simBinom Synthetic point-referenced binomial count data
simGaussian Synthetic point-referenced Gaussian data
simPoisson Synthetic point-referenced Poisson count data
sim_spData Simulate spatial data on unit square
sim_stvcPoisson Synthetic point-referenced spatial-temporal Poisson count data simulated using spatially-temporally varying coefficients
spGLMexact Univariate Bayesian spatial generalized linear model
spGLMstack Bayesian spatial generalized linear model using predictive stacking
spLMexact Univariate Bayesian spatial linear model
spLMstack Bayesian spatial linear model using predictive stacking
spStack spStack: Bayesian Geostatistics Using Predictive Stacking
stackedSampler Sample from the stacked posterior distribution
stvcGLMexact Bayesian spatially-temporally varying generalized linear model
stvcGLMstack Bayesian spatially-temporally varying coefficients generalized linear model using predictive stacking
surfaceplot Make a surface plot
surfaceplot2 Make two side-by-side surface plots