RandomFields

Simulation methods for Brown-Resnick processes

Bayesian Spatial Modelling

Documentation of some further changings

Coordinate systems

Methods for Gaussian Random Fields

Documentation of major changings

Information about the implemented covariance models

Transformation of coordinate systems

Constants used in RandomFields (RC constants)

Evaluation operators (RF commands)

Linear part of RMmodel

(Cross-)Covariance function

Covariance matrix

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

Evaluating distribution families

Class RFempVariog

Evaluate Covariance and Variogram Functions

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

Class RFfit

Optimisers for fitting model parameters to spatial data

RFformula - syntax to design random field models with trend or linear mixed models

Advanced RFformula

RFfractaldimension

Simulation Techniques

Internally stored model

Information on RMmodels

Names of implemented covariance and variogram models

Class RFgridDataFrame

Graphical User Interface For Fitting Covariance Models And Variograms

Hurst coefficient

Interpolation methods

Linear part of RMmodel

Likelihood and estimation of linear models

Empirical (Cross-)Madogram

RFoldstyle

Setting control arguments

Setting control arguments of RandomFields – advanced examples

Graphical parameters for plots

Class RFpointsDataFrame

Empirical Pseudomadogram

Pseudovariogram

Likelihood ratio test

Simulation of Random Fields

Further Examples for the Simulation of Random Fields

Sophisticated Examples for the Simulation of Random Fields

Simulation of Random Fields – Advanced

Class RFsp

Class "RFspatialGridDataFrame"

Class "RFspatialPointsDataFrame"

Empirical (Cross-)Variogram

Overview over classes of RMmodels

Scaling operator

Scaling operator – comments for advanced applications

Anisotropy matrix given by angle

Askey model

Space-time moving average model

RMball

Model bridging stationary and intrinsically stationary processes

Covariance Model for binary field based on a Gaussian field

Bessel Family Covariance Model

Bivariate Cauchy Model

Gneiting-Wendland Covariance Models

Bivariate stable Model

Full Bivariate Whittle Matern Model

Scale model for a few areas of different scales and/or differentiabilities

Transformation from Brown-Resnick to Bernoulli

Transformation from Brown-Resnick to Gauss

Tail correlation function of the Brown-Resnick process

Bubble model for arbitrary areas of scales

Cauchy Family Covariance Model

Modifications of the Cauchy Family Covariance Model

Schoenberg's representation for the classes psi_d and psi_{∞} in d=2

Circular Covariance Model

Covariance Matrix Constant in Space

Non-stationary covariance model corresponding to a variogram model

Model for covariates

Cox Isham Covariance Model

Cubic Covariance Model

Curlfree Covariance Model

Gneiting's modification towards finite range

Dagum Covariance Model Family

Exponentially Damped Cosine

Declaration of dummy variables for statistical inference

Bivariate Delay Effect

Gradient of a field

Modified De Wijsian Variogram Model

Divfree Covariance Model

Special models for rotation like fields

Generalized Cauchy Family Covariance Model

Exponential Covariance Model

Exponential operator

Variogram Model of Fractal Brownian Motion

Fixed Covariance Matrix

Fixed Effect Model

Fractionally Differenced Process Model

Fractal Gaussian Model Family

Gaussian Covariance Model

Generalized Cauchy Family Covariance Model

Generalized Fractal Brownian Motion Variogram Model

Gneiting-Wendland Covariance Models

Non-Separable Space-Time model

Gneiting Covariance Model

Gneiting Covariance Model Used as Tapering Function

Generalized Hyperbolic Covariance Model

Iaco-Cesare model

Identical Model

Identical Model

Internal models

Integral exponential operator

Intrinsic Embedding Covariance Model

Identical Model

Local-Global Distinguisher Family Covariance Model

Locally Positive Definite Function Given by the Fractal Brownian Motion

Ma operator

Ma-Stein operator

Whittle-Matern Covariance Model

Matrix operator

Covariance and Variogram Models in RandomFields (RM commands)

Class RMmodel

Class CLASS_FIT

Class RMmodelgenerator

Advanced features of the models

Auxiliary and other Models

Multivariate models

Non-stationary features of the models

Space-time Covariance Models

Covariance models valid on a sphere

Covariance models valid for max-stable random fields

Trend Modelling

Mixture of shape functions

multivariate quasi-arithmetic mean

Multiplication of Random Field Models

The Multiquadric Family Covariance Model on the Sphere

Natural scale

Non-stationary Whittle-Matern Covariance Model

Non-Separable Space-Time model

Nugget Effect Covariance Model

Variogram Model Similar to Fractal Brownian Motion

Parsimonious Multivariate Whittle Matern Model

Penta Covariance Model

Addition of Random Field Models

RMpolygon

Creating polynomial models

Power operator for Variograms and Covariance functions

Plain scalar product

Quasi-arithmetic mean

Variant of the exponential model

Rational function

Rotation matrices

Scale model for arbitrary areas of scales

Covariance Model for binary field based on Gaussian field

Schur product

Random sign

The Sinepower Covariance Model on the Sphere

The Spherical Covariance Model

Stable Family / Powered Exponential Model

Stein's non-separable space-time model

Single temporal process

Tail correlation function of the Brown-Resnick process

Plain scalar product

Turning Bands Method

Transformation of coordinate systems

Trend Model

Truncating the Support of a Shape Function

User-Defined Function

Vector Covariance Model

Wave Covariance Model / Cardinal Sine

Models for classes of random fields (RP commands)

Simulation of Binary Random Fields

Brown-Resnick process

Simulation of Chi2 Random Fields

Circulant Embedding methods

Random coin method

Methods relying on square roots of the covariance matrix

Simulation of Gaussian Random Fields

Hyperplane method

Simulation of Max-Stable Random Fields

Simulation examples of advanced Max-Stable Random Fields

Method to simulate the Nugget effect

Extremal t process

Simulation of Poisson Random Fields

Extremal Gaussian process

Methods relying on square roots of the covariance matrix

(Mixed) Moving Maxima

Methods that are specific to certain covariance models