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geostatsp (version 1.4.4)

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.

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Version

Install

install.packages('geostatsp')

Monthly Downloads

379

Version

1.4.4

License

GPL

Maintainer

Patrick Brown

Last Published

July 7th, 2016

Functions in geostatsp (1.4.4)

Linear Geostatistical Models

Valid models in INLA

Convert a raster to an im object

Exceedance probabilities

Evaluate the Matern correlation function

conditionalGmrf

Conditional distribution of GMRF

Spatial prediction, or Kriging

Likelihood Based Parameter Estimation for Gaussian Random Fields

Loaloa prevalence data from 197 village surveys

Simulate a log-Gaussian Cox process

Create a raster with square cells

Joint confidence regions

Precision matrix for a Matern spatial correlation

Sensitivity and specificity

Nearest neighbour matrices

Simulation of Random Fields

stackRasterList

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

Murder locations

Swiss rainfall data

Mercer and Hall wheat yield data

Raster of Swiss rain data

Compute Empirical Variograms and Permutation Envelopes

Generalized Linear Geostatistical Models