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| adjust.sigma2 | Adjustment factor for the variance of the convolution of Gaussian noise |
| autocor.plot | Plot of the autocorrelgram for posterior samples |
| binary.probit.Bayes | Bayesian estimation for the two-levels binary probit model |
| binomial.logistic.Bayes | Bayesian estimation for the binomial logistic model |
| binomial.logistic.MCML | Monte Carlo Maximum Likelihood estimation for the binomial logistic model |
| coef.PrevMap | Extract model coefficients |
| coef.PrevMap.ps | Extract model coefficients from geostatistical linear model with preferentially sampled locations |
| continuous.sample | Spatially continuous sampling |
| contour.pred.PrevMap | Contour plot of a predicted surface |
| control.mcmc.Bayes | Control settings for the MCMC algorithm used for Bayesian inference |
| control.mcmc.Bayes.SPDE | Control settings for the MCMC algorithm used for Bayesian inference using SPDE |
| control.mcmc.MCML | Control settings for the MCMC algorithm used for classical inference on a binomial logistic model |
| control.prior | Priors specification |
| control.profile | Auxliary function for controlling profile log-likelihood in the linear Gaussian model |
| create.ID.coords | ID spatial coordinates |
| data_sim | Simulated binomial data-set over the unit square |
| dens.plot | Density plot for posterior samples |
| discrete.sample | Spatially discrete sampling |
| galicia | Heavy metal biomonitoring in Galicia |
| galicia.boundary | Boundary of Galicia |
| glgm.LA | Maximum Likelihood estimation for generalised linear geostatistical models via the Laplace approximation |
| Laplace.sampling | Langevin-Hastings MCMC for conditional simulation |
| Laplace.sampling.lr | Langevin-Hastings MCMC for conditional simulation (low-rank approximation) |
| Laplace.sampling.SPDE | Independence sampler for conditional simulation of a Gaussian process using SPDE |
| linear.model.Bayes | Bayesian estimation for the geostatistical linear Gaussian model |
| linear.model.MLE | Maximum Likelihood estimation for the geostatistical linear Gaussian model |
| lm.ps.MCML | Monte Carlo Maximum Likelihood estimation of the geostatistical linear model with preferentially sampled locations |
| loaloa | Loa loa prevalence data from 197 village surveys |
| loglik.ci | Profile likelihood confidence intervals |
| loglik.linear.model | Profile log-likelihood or fixed parameters likelihood evaluation for the covariance parameters in the geostatistical linear model |
| matern.kernel | Matern kernel |
| plot.pred.PrevMap | Plot of a predicted surface |
| plot.pred.PrevMap.ps | Plot of a predicted surface of geostatistical linear fits with preferentially sampled locations |
| plot.PrevMap.diagnostic | Plot of the variogram-based diagnostics |
| plot.profile.PrevMap | Plot of the profile log-likelihood for the covariance parameters of the Matern function |
| plot.shape.matern | Plot of the profile likelihood for the shape parameter of the Matern covariance function |
| point.map | Point map |
| poisson.log.MCML | Monte Carlo Maximum Likelihood estimation for the Poisson model |
| set.par.ps | Define the model coefficients of a geostatistical linear model with preferentially sampled locations |
| shape.matern | Profile likelihood for the shape parameter of the Matern covariance function |
| spat.corr.diagnostic | Diagnostics for residual spatial correlation |
| spatial.pred.binomial.Bayes | Bayesian spatial prediction for the binomial logistic and binary probit models |
| spatial.pred.binomial.MCML | Spatial predictions for the binomial logistic model using plug-in of MCML estimates |
| spatial.pred.linear.Bayes | Bayesian spatial predictions for the geostatistical Linear Gaussian model |
| spatial.pred.linear.MLE | Spatial predictions for the geostatistical Linear Gaussian model using plug-in of ML estimates |
| spatial.pred.lm.ps | Spatial predictions for the geostatistical Linear Gaussian model using plug-in of ML estimates |
| spatial.pred.poisson.MCML | Spatial predictions for the Poisson model with log link function, using plug-in of MCML estimates |
| summary.Bayes.PrevMap | Summarizing Bayesian model fits |
| summary.PrevMap | Summarizing likelihood-based model fits |
| summary.PrevMap.ps | Summarizing fits of geostatistical linear models with preferentially sampled locations |
| trace.plot | Trace-plots for posterior samples |
| trace.plot.MCML | Trace-plots of the importance sampling distribution samples from the MCML method |
| trend.plot | Plot of trends |
| variog.diagnostic.glgm | Variogram-based validation for generalized linear geostatistical model fits (Binomial and Poisson) |
| variog.diagnostic.lm | Variogram-based validation for linear geostatistical model fits |
| variogram | The empirical variogram |