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geostatsp (version 1.3.5)

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

1.3.5

License

GPL

Maintainer

Patrick Brown

Last Published

August 17th, 2015

Functions in geostatsp (1.3.5)

glgm-methods

Generalized Linear Geostatistical Models
conditionalGmrf

Conditional distribution of GMRF
maternGmrfPrec

Precision matrix for a Matern spatial correlation
squareRaster

Create a raster with square cells
rongelapUTM

Rongelap data
likfitLgm

Likelihood Based Parameter Estimation for Gaussian Random Fields
nn32

Nearest neighbour matrices
RFsimulate

Simulation of Random Fields
swissRainR

Raster of Swiss rain data
excProb

Exceedance probabilities
wheat

Mercer and Hall wheat yield data
asImRaster

Convert a raster to an im object
murder

Murder locations
spatialRoc

Sensitivity and specificity
stackRasterList

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

Linear Geostatistical Models
krigeLgm

Spatial prediction, or Kriging
profLlgm

Joint confidence regions
matern

Evaluate the Matern correlation function
loaloa

Loaloa prevalence data from 197 village surveys
swissRain

Swiss rainfall data
simLgcp

Simulate a log-Gaussian Cox process
inla.models

Valid models in INLA
gambiaUTM

Gambia data
variog

Compute Empirical Variograms and Permutation Envelopes