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RandomFields (version 3.1.16)

Simulation and Analysis of Random Fields

Description

Methods for the inference on and the simulation of Gaussian fields are provided, as well as methods for the simulation of extreme value random fields.

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Version

Install

install.packages('RandomFields')

Monthly Downloads

1,209

Version

3.1.16

License

GPL (>= 3)

Maintainer

Martin Schlather

Last Published

June 23rd, 2016

Functions in RandomFields (3.1.16)

Hierarchical Modelling

Bayesian Spatial Modelling

Fast and Exact Simulation of Large Gaussian Lattice Systems in R2

Coordinate systems

Coordinate systems

Covariance models for multivariate and vector valued fields

Internal functions

Internal functions

Obsolete Functions

Obsolete functions

Papers involving RandomFields and co-authored by M. Schlather

conventional2RFspDataFrame

Coercion to class 'RFsp' objects

Brown-Resnick-Specific

Simulation methods for Brown-Resnick processes

Documentation of some further changings

On some covariance models based on normal scale mixtures

Models for stationary max-stable random fields

Systematic co-occurrence of tail correlation functions among max-stable processes

Methods for function plot in package RandomFields

Evaluation operators (RF commands)

Mathematial C functions

Transformation of coordinate systems

Information about the implemented covariance models

Covariance Models for Random Vector Fields

RandomFields-package

Simulation and Analysis of Random Fields

Constants used in RandomFields (RC constants)

Optimisers for fitting model parameters to spatial data

Linear part of RMmodel

Fitting model parameters to spatial data (regionalised variables) and to linear (mixed) models

Internally stored model

RFempVariog-class

Class RFempVariog

Evaluate Covariance and Variogram Functions

RFgetMethodNames

Simulation Techniques

Evaluating distribution families

RFempiricalvariogram

Empirical (Cross-)Variogram

Hurst coefficient

Graphical parameters for plots

Information on RMmodels

RFsimulate.sophisticated.examples

Sophisticated Examples for the Simulation of Random Fields

Anisotropy matrix given by angle

RFgridDataFrame-class

Class RFgridDataFrame

RFsimulate.more.examples

Further Examples for the Simulation of Random Fields

Simulation of Random Fields

RMmodels Overview

Overview over classes of RMmodels

Graphical User Interface For Fitting Covariance Models And Variograms

Linear part of RMmodel

RFoptionsAdvanced

Setting control arguments of RandomFields -- advanced examples

Covariance Model for binary field based on a Gaussian field

Circular Covariance Model

Model for covariates

Modifications of the Cauchy Family Covariance Model

Coordinates in the mixed model representation

RFloglikelihood

Likelihood and estimation of linear models

Cubic Covariance Model

Space-time moving average model

RFgetModelNames

Names of implemented covariance and variogram models

Special models for rotation like fields

Generalized Cauchy Family Covariance Model

Generalized Cauchy Family Covariance Model

Local-Global Distinguisher Family Covariance Model

Identical Model

Integral exponential operator

Internal models

Generalized Fractal Brownian Motion Variogram Model

Identical Model

Gneiting-Wendland Covariance Models

Model bridging stationary and intrinsically stationary processes

RFspatialPointsDataFrame-class

Class "RFspatialPointsDataFrame"

RFpointsDataFrame-class

Class RFpointsDataFrame

Gneiting Covariance Model

Covariance Matrix Constant in Space

Generalized Hyperbolic Covariance Model

Cauchy Family Covariance Model

Bessel Family Covariance Model

Matrix operator

Dagum Covariance Model Family

RMmodelsSpacetime

Space-time Covariance Models

RMmodelsMultivariate

Multivariate models

RMmodelFit-class

Class "RMmodelFit"

Ma-Stein operator

Multiplication of Random Field Models

RMmodelsAdvanced

Advanced features of the mdoels

Penta Covariance Model

Exponential Covariance Model

Addition of Random Field Models

Fractionally Differenced Process Model

Gaussian Covariance Model

The Multiquadric Family Covariance Model on th Sphere

Mixture of shape functions

Trend Modelling

Trend Modelling

Creating poylonmial models

Power operator for Variograms and Covariance functions

Stable Family / Powered Exponential Model

Fractal Gaussian Model Family

The Sinepower Covariance Model on the Sphere

Exponentially Damped Cosine

Fixed Covariance Matrix

RMmodelsNonstationary

Nonstationary features of the mdoels

Modified DeWijsian Variogram Model

Strokorb's Functions

Tail correlation function of the Brown-Resnick process

Wave Covariance Model / Cardinal Sine

Brown-Resnick process

Simulation of a Chi2 Random Fields

Auxiliary and other Models

User Defined Function

Transformation of coordinate systems

Turning Bands Method

Class RMmodel

RMwhittlematern

Whittle-Matern Covariance Model

Max-stable random fields

Simulation of Max-Stable Random Fields

Plain scalar product

Simulation of Random Fields

Circulant Embedding

Circulant Embedding methods

Simulation of Gaussian Random Fields

Random scaling used with balls

Random coin method

Turning Bands method

Simulation of a T Random Fields

Methods relying on square roots of the covariance matrix

The Spherical Covariance Model

(Mixed) Moving Maxima

Plain scalar product

Quasi-arithmetic mean

Stein nonseparable space-time model

Hyperplane method

Simulation of Binary Random Fields

Models for classes of random fields (RP commands)

Independent Variables

Method to simulate the Nugget effect

Random scaling used with balls

Random scaling used with balls

Max-stable random fields, advanced

Simulation examples of advanced Max-Stable Random Fields

ExtremalGaussian

Extremal Gaussian process

Extremal t process

Random scaling used with balls

Methods that are specific to certain covariance models

Random scaling used with balls

Spectral turning bands method

Pressure and temperature forecast errors over the Pacific Northwest

Transformation of an 'sp' object to an 'RFsp' object

Random scaling used with balls

Soil data of North Bavaria, Germany