RandomFields (version 1.3.27)

SimulateRF: Simulation of Random Fields

Description

DoSimulateRF performs an already initialised simulation. InitSimulateRF internal function; use InitGaussRF and InitMaxStableRF, instead.

Usage

DoSimulateRF(n=1, register=0, paired=FALSE)
InitSimulateRF(x, y=NULL, z=NULL, T=NULL, grid, model, param, trend,
               method=NULL, register=0, gridtriple=FALSE, distribution=NA)

Arguments

x

matrix of coordinates, or vector of x coordinates

y

vector of y coordinates

z

vector of z coordinates

T

time instances

grid

logical; determines whether the vectors x, y, and z should be interpreted as a grid definition, see Details.

model

string; covariance or variogram model, see CovarianceFct, or type PrintModelList() to get all options

param

vector or list. param=c(mean, variance, nugget, scale, ...), param=list(c(variance, scale, ...), ..., c(variance,scale,...)), param=matrix(...), or param=list(list(variance, anisotropy,

trend

Not programmed yet. trend surface: number (mean), vector of length $d+1$ (linear trend $a_0+a_1 x_1 + \ldots + a_d x_d$), or function

method

NULL or string; Method used for simulating, see RFMethods, or type PrintMethodList() to get all optio

register

0:9; place where intermediate calculations are stored; the numbers are aliases for 10 internal registers

gridtriple

logical; if gridtriple==FALSE ascending sequences for the parameters x, y, and z are expected; if gridtriple==TRUE triples of form c(start,end,step) expec

distribution

marginal distribution: 'Gauss', 'Poisson', or 'MaxStable'

n

number of realisations to generate; if paired=TRUE then n must be even.

paired

logical. paired may be TRUE only for the simulation of Gaussian random fields. If TRUE then every second simulation is obtained by only changing the signs of the standard Gaussian random variables, the

Value

• InitSimulateRF returns 0 if no error has occurred during the initialisation process, and a positive value if failed. DoSimulateRF returns NULL if an error has occurred; otherwise the returned object depends on the parameters n and grid: n==1: * grid==FALSE. A vector of simulated values is returned (independent of the dimension of the random field) * grid==TRUE. An array of the dimension of the random field is returned. n>1: * grid==FALSE. A matrix is returned. The columns contain the repetitions. * grid==TRUE. An array of dimension $d+1$, where $d$ is the dimension of the random field, is returned. The last dimension contains the repetitions.

See Also

GaussRF, MaxStableRF, RandomFields