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geostatsp (version 2.0.6)

Geostatistical Modelling with Likelihood and Bayes

Description

Geostatistical modelling facilities using 'SpatRaster' and 'SpatVector' objects are provided. Non-Gaussian models are fit using 'INLA', and Gaussian geostatistical models use Maximum Likelihood Estimation. For details see Brown (2015) . The 'RandomFields' package is available at .

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Version

Install

install.packages('geostatsp')

Monthly Downloads

700

Version

2.0.6

License

GPL

Maintainer

Last Published

February 20th, 2024

Functions in geostatsp (2.0.6)

Loaloa prevalence data from 197 village surveys

Valid models in INLA

Linear Geostatistical Models

Joint confidence regions

Exponentiate posterior quantiles

Evaluate the Matern correlation function

Precision matrix for a Matern spatial correlation

stackRasterList

Converts a list of rasters, possibly with different projections and resolutions, to a single raster stack.

Simulate a log-Gaussian Cox process

squareRaster-methods

Create a raster with square cells

Sensitivity and specificity

Swiss rainfall data

Mercer and Hall wheat yield data

Raster of Swiss rain data

conditionalGmrf

Conditional distribution of GMRF

Compute Empirical Variograms and Permutation Envelopes

Murder locations

PC prior for range parameter

Simulation of Random Fields

Generalized Linear Geostatistical Models

Exceedance probabilities

Spatial prediction, or Kriging

Likelihood Based Parameter Estimation for Gaussian Random Fields