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geostatsp (version 1.8.6)

Geostatistical Modelling with Likelihood and Bayes

Description

Geostatistical modelling facilities using 'Raster' and 'SpatialPoints' objects are provided. Non-Gaussian models are fit using 'INLA', and Gaussian geostatistical models use Maximum Likelihood Estimation. For details see Brown (2015) .

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Version

Install

install.packages('geostatsp')

Monthly Downloads

379

Version

1.8.6

License

GPL

Maintainer

Patrick Brown

Last Published

October 5th, 2021

Functions in geostatsp (1.8.6)

Exceedance probabilities

Convert a raster to an im object

Spatial prediction, or Kriging

Valid models in INLA

conditionalGmrf

Conditional distribution of GMRF

Generalized Linear Geostatistical Models

Linear Geostatistical Models

Likelihood Based Parameter Estimation for Gaussian Random Fields

Simulation of Random Fields

Joint confidence regions

Simulate a log-Gaussian Cox process

Evaluate the Matern correlation function

Loaloa prevalence data from 197 village surveys

Sensitivity and specificity

Raster of Swiss rain data

Swiss rainfall data

Precision matrix for a Matern spatial correlation

Murder locations

Mercer and Hall wheat yield data

Exponentiate posterior quantiles

Compute Empirical Variograms and Permutation Envelopes

PC prior for range parameter

squareRaster-methods

Create a raster with square cells

stackRasterList

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