RandomFields (version 3.1.12)

Obsolete Functions: Obsolete functions

Description

This part gives the obsolete functions of RandomFields Version 2 that are not maintained anymore.

Usage

Covariance(x, y = NULL, model, param = NULL, dim = if
 (!missing(Distances)) { if (is.matrix(x)) ncol(x) else 1},
 Distances, fctcall = c("Cov", "Variogram", "CovMatrix"))
CovarianceFct(x, y = NULL, model, param = NULL, dim = if
 (!missing(Distances)) { if (is.matrix(x)) ncol(x) else 1},
 Distances, fctcall = c("Cov", "Variogram", "CovMatrix"))
CovMatrix(x, y = NULL, model, param = NULL, dim = if
 (!missing(Distances)) { if (is.matrix(x)) ncol(x) else 1}, Distances)
DeleteAllRegisters()
DeleteRegister(nr=0)
DoSimulateRF(n = 1, register = 0, paired=FALSE, trend=NULL) 
InitSimulateRF(x, y = NULL, z = NULL, T=NULL, grid=!missing(gridtriple),
 model, param, trend, method = NULL, register = 0,
 gridtriple, distribution=NA)
InitGaussRF(x, y = NULL, z = NULL, T=NULL, grid=!missing(gridtriple),
 model, param, trend=NULL, method = NULL, register = 0, gridtriple) 
GaussRF(x, y = NULL, z = NULL, T=NULL, grid=!missing(gridtriple), model,
 param, trend=NULL, method = NULL, n = 1, register = 0, gridtriple,
 paired=FALSE, PrintLevel=1, Storing=TRUE, ...) 
Variogram(x, model, param = NULL, dim = if (!missing(Distances))
 { if (is.matrix(x)) ncol(x) else 1}, Distances)
InitMaxStableRF(x, y = NULL, z = NULL, grid=NULL, model, param, maxstable,
 method = NULL, register = 0, gridtriple = FALSE)
MaxStableRF(x, y = NULL, z = NULL, grid=NULL, model, param, maxstable,
 method = NULL, n = 1, register = 0, gridtriple = FALSE, ...)
EmpiricalVariogram(x, y = NULL, z = NULL, T=NULL, data, grid=NULL, bin,
 gridtriple = FALSE, phi, theta, deltaT)
Kriging(krige.method, x, y=NULL, z=NULL, T=NULL, grid=NULL, gridtriple=FALSE,
 model, param, given, data, trend=NULL,pch=".", return.variance=FALSE,
 allowdistanceZero = FALSE, cholesky=FALSE) 
CondSimu(krige.method, x, y=NULL, z=NULL, T=NULL, grid=NULL, gridtriple=FALSE,
 model, param, method=NULL, given, data, trend=NULL, n=1, register=0, 
 err.model=NULL, err.param=NULL, err.method=NULL, err.register=1, 
 tol=1E-5, pch=".", paired=FALSE, na.rm=FALSE) 
RFparameters(...)
hurst(x, y = NULL, z = NULL, data, gridtriple = FALSE, sort=TRUE,
 block.sequ = unique(round(exp(seq(log(min(3000, dim[1] / 5)),
 log(dim[1]), len=min(100, dim[1]))))),
 fft.m = c(1, min(1000, (fft.len - 1) / 10)),
 fft.max.length = Inf, 
 method=c("dfa", "fft", "var"), mode=c("plot", "interactive"), pch=16, cex=0.2, cex.main=0.85,
 PrintLevel=RFoptions()$general$printlevel,height=3.5, ...)
fractal.dim(x, y = NULL, z = NULL, data, grid=TRUE, gridtriple = FALSE,
 bin, vario.n=5, sort=TRUE, fft.m = c(65, 86), fft.max.length=Inf,
 fft.max.regr=150000, fft.shift = 50, method=c("variogram", "fft"),
 mode=c("plot", "interactive"), pch=16, cex=0.2, cex.main=0.85, PrintLevel = RFoptions()$general$printlevel, height=3.5, ...)
fitvario(x, y=NULL, z=NULL, T=NULL, data, model, param, lower=NULL,
 upper=NULL, sill=NA, grid=!missing(gridtriple), gridtriple=FALSE, ...)

Arguments

x, y, model, param, dim, Distances, fctcall, n, register, paired, trend, z, T, grid, method, gridtriple, distribution, PrintLevel, Storing, ..., maxstable, data, bin, phi, theta, deltaT, krige.method, pch, return.variance, allowdistanceZero, cholesky

as the functions are obsolete, all these arguments are not documented anymore.

Value

• See ../doc/version.pdf{version2} for details on these obsolete commands.

See Also

The functions that should be used instead are, for instance, RFcov, RFcovmatrix, RFvariogram, RFsimulate, RFinterpolate, RFempiricalvariogram, RFfit, RFoptions, RFhurst, RFfractaldim

See ../doc/version.pdf{version2} for details on the obsolete commands.

Examples

RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
##                   RFoptions(seed=NA) to make them all random again



## no examples given, as command is obsolete
\dontrun{ # ok
\dontshow{StartExample()}
x <- seq(0, 5, 0.05) 
model <- "exp"
param <- c(0, 1, 0, 1)

plot(x, Covariance(x, model=model, param=param))
plot(x, Variogram(x, model=model, param=param))

z <- GaussRF(x, model=model, param=param)
plot(x, z, type="l")

z <- GaussRF(x=x, y=x, model=model, param=param, grid=TRUE)
image(x, x, z)
EmpiricalVariogram(x, x, data=z)

g1 <- runif(5) * 2
g2 <- runif(5) * 2
z <- GaussRF(g1, g2, grid=FALSE, model=model, param=param)
k <- Kriging("S", x, x, given=cbind(g1, g2),
        data=z, model=model, param=param)
Print(range(z), range(k))
col <- rainbow(20)
zlim <- range(z, k)
image(x, x, k, col=col, zlim=zlim)
points(g1, g2, pch=20,cex=2)
points(g1, g2, pch=16, col=col[pmax(1, (z-zlim[1]) / diff(zlim) * 20 )])
#
estparam <- rep(NA, 4)
v <- fitvario(x=g1, y=g2, grid=FALSE, model=model, param=estparam, data=z)
Print(v$ml, v$ml$ml.value)
}
FinalizeExample()