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georob (version 0.3-8)

Robust Geostatistical Analysis of Spatial Data

Description

Provides functions for efficiently fitting linear models with spatially correlated errors by robust and Gaussian (Restricted) Maximum Likelihood and for computing robust and customary point and block external-drift Kriging predictions, along with utility functions for variogram modelling in ad hoc geostatistical analyses, model building, model evaluation by cross-validation, (conditional) simulation of Gaussian processes, unbiased back-transformation of Kriging predictions of log-transformed data.

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Version

Install

install.packages('georob')

Monthly Downloads

406

Version

0.3-8

License

GPL (>= 2)

Maintainer

Andreas Papritz

Last Published

March 29th, 2019

Functions in georob (0.3-8)

cv

Generic Cross-validation
cv.georob

Cross-Validating a Spatial Linear Model Fitted by georob
control.georob

Tuning Parameters for georob
profilelogLik

Profile Likelihood
georobPackage

The georob Package
sample.variogram

Computing (Robust) Sample Variograms of Spatial Data
georobS3methods

Common S3 Methods for Class georob
fit.variogram.model

Fitting Model Functions to Sample Variograms
georob

Robust Fitting of Spatial Linear Models
pmm

Parallelized Matrix Multiplication
georobSimulation

Simulating Realizations of Gaussian Processes from Object of Class georob
internal.functions

Internal Functions of Package georob
param.names

Names and Permissible Ranges of Variogram Parameters
plot.georob

Plot Methods for Class georob
predict.georob

Predict Method for Robustly Fitted Spatial Linear Models
georobModelBuilding

S3 Methods for Stepwise Building Fixed-Effects Models for Class georob
georobObject

Fitted georob Object
lgnpp

Unbiased Back-Transformations for Log-normal Kriging
validate.predictions

Summary Statistics of (Cross-)Validation Prediction Errors
default.aniso

Setting Default Values of Variogram Parameters
compress

Compact Storage of Symmetric and Triangular Matrices