candidateModels         Create a collection of candidate models for
                        stacking
cholUpdate              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-package         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
