# Geostatistical Modelling of Spatially Referenced Prevalence Data

## Documentation for package ‘PrevMap’ version 1.5

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

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 | Monte Carlo Maximum Likelihood estimation for the binomial logistic model
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