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geostatsp (version 1.1.9)

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

521

Version

1.1.9

License

GPL

Maintainer

Patrick Brown

Last Published

January 23rd, 2015

Functions in geostatsp (1.1.9)

excProb

Exceedance probabilities
murder

Murder locations
glgm-methods

Generalized Linear Geostatistical Models
squareRaster

Create a raster with square cells
asImRaster

Convert a raster to an im object
wheat

Mercer and Hall wheat yield data
krigeLgm

Spatial prediction, or Kriging
matern

Evaluate the Matern correlation function
likfitLgm

Likelihood Based Parameter Estimation for Gaussian Random Fields
inla.models

Valid models in INLA
nn32

Nearest neighbour matrices
spatialRoc

Sensitivity and specificity
RFsimulate

Simulation of Random Fields
variog

Compute Empirical Variograms and Permutation Envelopes
loaloa

Loaloa prevalence data from 197 village surveys
swissRainR

Raster of Swiss rain data
swissRain

Swiss rainfall data
gambiaUTM

Gambia data
lgm-methods

Linear Geostatistical Models
simLgcp

Simulate a log-Gaussian Cox process
conditionalGmrf

Conditional distribution of GMRF
rongelapUTM

Rongelap data
maternGmrfPrec

Precision matrix for a Matern spatial correlation
profLlgm

Joint confidence regions
stackRasterList

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