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PrevMap (version 1.5)

Geostatistical Modelling of Spatially Referenced Prevalence Data

Description

Provides functions for both likelihood-based and Bayesian analysis of spatially referenced prevalence data, and is also an extension of the 'geoR' package.

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Version

Install

install.packages('PrevMap')

Monthly Downloads

334

Version

1.5

License

GPL (>= 2)

Maintainer

Emanuele Giorgi

Last Published

April 24th, 2019

Functions in PrevMap (1.5)

adjust.sigma2

Adjustment factor for the variance of the convolution of Gaussian noise
control.mcmc.Bayes

Control settings for the MCMC algorithm used for Bayesian inference
variog.diagnostic.glgm

Variogram-based validation for generalized linear geostatistical model fits (Binomial and Poisson)
plot.shape.matern

Plot of the profile likelihood for the shape parameter of the Matern covariance function
plot.profile.PrevMap

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

Plot of trends
control.profile

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

Spatially discrete sampling
contour.pred.PrevMap

Contour plot of a predicted surface
continuous.sample

Spatially continuous sampling
summary.PrevMap.ps

Summarizing fits of geostatistical linear models with preferentially sampled locations
control.mcmc.MCML

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

Summarizing likelihood-based model fits
galicia

Heavy metal biomonitoring in Galicia
data_sim

Simulated binomial data-set over the unit square
dens.plot

Density plot for posterior samples
control.mcmc.Bayes.SPDE

Control settings for the MCMC algorithm used for Bayesian inference using SPDE
control.prior

Priors specification
lm.ps.MCML

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

Profile log-likelihood or fixed parameters likelihood evaluation for the covariance parameters in the geostatistical linear model
create.ID.coords

ID spatial coordinates
loglik.ci

Profile likelihood confidence intervals
linear.model.Bayes

Bayesian estimation for the geostatistical linear Gaussian model
galicia.boundary

Boundary of Galicia
linear.model.MLE

Maximum Likelihood estimation for the geostatistical linear Gaussian model
matern.kernel

Matern kernel
plot.PrevMap.diagnostic

Plot of the variogram-based diagnostics
loaloa

Loa loa prevalence data from 197 village surveys
plot.pred.PrevMap.ps

Plot of a predicted surface of geostatistical linear fits with preferentially sampled locations
spatial.pred.linear.MLE

Spatial predictions for the geostatistical Linear Gaussian model using plug-in of ML estimates
plot.pred.PrevMap

Plot of a predicted surface
spatial.pred.lm.ps

Spatial predictions for the geostatistical Linear Gaussian model using plug-in of ML estimates
spat.corr.diagnostic

Diagnostics for residual spatial correlation
glgm.LA

Monte Carlo Maximum Likelihood estimation for the binomial logistic model
set.par.ps

Define the model coefficients of a geostatistical linear model with preferentially sampled locations
spatial.pred.binomial.Bayes

Bayesian spatial prediction for the binomial logistic and binary probit models
trace.plot.MCML

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

Point map
trace.plot

Trace-plots for posterior samples
poisson.log.MCML

Monte Carlo Maximum Likelihood estimation for the Poisson model
spatial.pred.binomial.MCML

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

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
spatial.pred.linear.Bayes

Bayesian spatial predictions for the geostatistical Linear Gaussian model
summary.Bayes.PrevMap

Summarizing Bayesian model fits
variog.diagnostic.lm

Variogram-based validation for linear geostatistical model fits
variogram

The empirical variogram
coef.PrevMap

Extract model coefficients
autocor.plot

Plot of the autocorrelgram for posterior samples
binary.probit.Bayes

Bayesian estimation for the two-levels binary probit model
Laplace.sampling

Langevin-Hastings MCMC for conditional simulation
Laplace.sampling.SPDE

Independence sampler for conditional simulation of a Gaussian process using SPDE
coef.PrevMap.ps

Extract model coefficients from geostatistical linear model with preferentially sampled locations
Laplace.sampling.lr

Langevin-Hastings MCMC for conditional simulation (low-rank approximation)
binomial.logistic.MCML

Monte Carlo Maximum Likelihood estimation for the binomial logistic model
binomial.logistic.Bayes

Bayesian estimation for the binomial logistic model