Geostatistical Modelling of Spatially Referenced Prevalence Data
Adjustment factor for the variance of the convolution of Gaussian nois...
Plot of the autocorrelgram for posterior samples
Bayesian estimation for the two-levels binary probit model
Bayesian estimation for the binomial logistic model
Monte Carlo Maximum Likelihood estimation for the binomial logistic mo...
Extract model coefficients from geostatistical linear model with prefe...
Extract model coefficients
Spatially continuous sampling
Contour plot of a predicted surface
Control settings for the MCMC algorithm used for Bayesian inference
Control settings for the MCMC algorithm used for Bayesian inference us...
Control settings for the MCMC algorithm used for classical inference o...
Priors specification
Auxliary function for controlling profile log-likelihood in the linear...
ID spatial coordinates
Density plot for posterior samples
Spatially discrete sampling
Maximum Likelihood estimation for generalised linear geostatistical mo...
Langevin-Hastings MCMC for conditional simulation (low-rank approximat...
Langevin-Hastings MCMC for conditional simulation
Independence sampler for conditional simulation of a Gaussian process ...
Bayesian estimation for the geostatistical linear Gaussian model
Maximum Likelihood estimation for the geostatistical linear Gaussian m...
Monte Carlo Maximum Likelihood estimation of the geostatistical linear...
Profile likelihood confidence intervals
Profile log-likelihood or fixed parameters likelihood evaluation for t...
Matern kernel
Plot of a predicted surface of geostatistical linear fits with prefere...
Plot of a predicted surface
Plot of the variogram-based diagnostics
Plot of the profile log-likelihood for the covariance parameters of th...
Plot of the profile likelihood for the shape parameter of the Matern c...
Point map
Monte Carlo Maximum Likelihood estimation for the Poisson model
Define the model coefficients of a geostatistical linear model with pr...
Profile likelihood for the shape parameter of the Matern covariance fu...
Diagnostics for residual spatial correlation
Bayesian spatial prediction for the binomial logistic and binary probi...
Spatial predictions for the binomial logistic model using plug-in of M...
Bayesian spatial predictions for the geostatistical Linear Gaussian mo...
Spatial predictions for the geostatistical Linear Gaussian model using...
Spatial predictions for the geostatistical Linear Gaussian model using...
Spatial predictions for the Poisson model with log link function, usin...
Summarizing Bayesian model fits
Summarizing fits of geostatistical linear models with preferentially s...
Summarizing likelihood-based model fits
Trace-plots of the importance sampling distribution samples from the M...
Trace-plots for posterior samples
Plot of trends
Variogram-based validation for generalized linear geostatistical model...
Variogram-based validation for linear geostatistical model fits
The empirical variogram
Provides functions for both likelihood-based and Bayesian analysis of spatially referenced prevalence data. For a tutorial on the use of the R package, see Giorgi and Diggle (2017) <doi:10.18637/jss.v078.i08>.