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PrevMap (version 1.5.3)

Geostatistical Modelling of Spatially Referenced Prevalence Data

Description

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) .

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Version

Install

install.packages('PrevMap')

Monthly Downloads

334

Version

1.5.3

License

GPL (>= 2)

Maintainer

Emanuele Giorgi

Last Published

February 6th, 2020

Functions in PrevMap (1.5.3)

binomial.logistic.Bayes

Bayesian estimation for the binomial logistic model

Plot of the autocorrelgram for posterior samples

binomial.logistic.MCML

Monte Carlo Maximum Likelihood estimation for the binomial logistic model

binary.probit.Bayes

Bayesian estimation for the two-levels binary probit model

Laplace.sampling.lr

Langevin-Hastings MCMC for conditional simulation (low-rank approximation)

Laplace.sampling

Langevin-Hastings MCMC for conditional simulation

Adjustment factor for the variance of the convolution of Gaussian noise

Laplace.sampling.SPDE

Independence sampler for conditional simulation of a Gaussian process using SPDE

Extract model coefficients

coef.PrevMap.ps

Extract model coefficients from geostatistical linear model with preferentially sampled locations

Density plot for posterior samples

Simulated binomial data-set over the unit square

control.profile

Auxliary function for controlling profile log-likelihood in the linear Gaussian model

create.ID.coords

ID spatial coordinates

control.mcmc.MCML

Control settings for the MCMC algorithm used for classical inference on a binomial logistic model

Priors specification

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

Profile likelihood confidence intervals

loglik.linear.model

Profile log-likelihood or fixed parameters likelihood evaluation for the covariance parameters in the geostatistical linear model

plot.profile.PrevMap

Plot of the profile log-likelihood for the covariance parameters of the Matern function

Monte Carlo Maximum Likelihood estimation of the geostatistical linear model with preferentially sampled locations

continuous.sample

Spatially continuous sampling

Loa loa prevalence data from 197 village surveys

plot.shape.matern

Plot of the profile likelihood for the shape parameter of the Matern covariance function

contour.pred.PrevMap

Contour plot of a predicted surface

plot.pred.PrevMap

Plot of a predicted surface

spatial.pred.linear.MLE

Spatial predictions for the geostatistical Linear Gaussian model using plug-in of ML estimates

plot.pred.PrevMap.ps

Plot of a predicted surface of geostatistical linear fits with preferentially sampled locations

spat.corr.diagnostic

Diagnostics for residual spatial correlation

spatial.pred.binomial.Bayes

Bayesian spatial prediction for the binomial logistic and binary probit models

linear.model.Bayes

Bayesian estimation for the geostatistical linear Gaussian model

Maximum Likelihood estimation for generalised linear geostatistical models via the Laplace approximation

spatial.pred.lm.ps

Spatial predictions for the geostatistical Linear Gaussian model using plug-in of ML estimates

galicia.boundary

Boundary of Galicia

linear.model.MLE

Maximum Likelihood estimation for the geostatistical linear Gaussian model

The empirical variogram

variog.diagnostic.lm

Variogram-based validation for linear geostatistical model fits

discrete.sample

Spatially discrete sampling

poisson.log.MCML

Monte Carlo Maximum Likelihood estimation for the Poisson model

plot.PrevMap.diagnostic

Plot of the variogram-based diagnostics

spatial.pred.linear.Bayes

Bayesian spatial predictions for the geostatistical Linear Gaussian model

spatial.pred.binomial.MCML

Spatial predictions for the binomial logistic model using plug-in of MCML estimates

Define the model coefficients of a geostatistical linear model with preferentially sampled locations

Heavy metal biomonitoring in Galicia

summary.PrevMap.ps

Summarizing fits of geostatistical linear models with preferentially sampled locations

summary.PrevMap

Summarizing likelihood-based model fits

trace.plot.MCML

Trace-plots of the importance sampling distribution samples from the MCML method

Profile likelihood for the shape parameter of the Matern covariance function

spatial.pred.poisson.MCML

Spatial predictions for the Poisson model with log link function, using plug-in of MCML estimates

Trace-plots for posterior samples

summary.Bayes.PrevMap

Summarizing Bayesian model fits

variog.diagnostic.glgm

Variogram-based validation for generalized linear geostatistical model fits (Binomial and Poisson)