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geostatsp (version 1.3.4)

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

367

Version

1.3.4

License

GPL

Maintainer

Patrick Brown

Last Published

July 7th, 2015

Functions in geostatsp (1.3.4)

variog

Compute Empirical Variograms and Permutation Envelopes
inla.models

Valid models in INLA
wheat

Mercer and Hall wheat yield data
matern

Evaluate the Matern correlation function
conditionalGmrf

Conditional distribution of GMRF
rongelapUTM

Rongelap data
loaloa

Loaloa prevalence data from 197 village surveys
nn32

Nearest neighbour matrices
simLgcp

Simulate a log-Gaussian Cox process
gambiaUTM

Gambia data
swissRainR

Raster of Swiss rain data
squareRaster

Create a raster with square cells
glgm-methods

Generalized Linear Geostatistical Models
murder

Murder locations
swissRain

Swiss rainfall data
spatialRoc

Sensitivity and specificity
maternGmrfPrec

Precision matrix for a Matern spatial correlation
likfitLgm

Likelihood Based Parameter Estimation for Gaussian Random Fields
stackRasterList

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

Joint confidence regions
lgm-methods

Linear Geostatistical Models
RFsimulate

Simulation of Random Fields
excProb

Exceedance probabilities
krigeLgm

Spatial prediction, or Kriging
asImRaster

Convert a raster to an im object