compositions (version 1.40-2)

CompLinModCoReg: Compositional Linear Model of Coregionalisation

Description

Creates a Variogram model according to the linear model of spatial corregionalisation for a compositional geostatistical analysis.

Usage

CompLinModCoReg(formula,comp,D=ncol(comp),envir=environment(formula))

Arguments

formula

A formula without left side providing a formal description of a variogram model.

comp

a compositional dataset, needed to provide the frame size

D

The dimension of the multivariate dataset

envir

The enviroment in which formula should be interpreted.

Value

A variogram function.

Details

The linear model of coregionalisation says uses the fact, that sums of valid variogram models are valid variograms and that skalar variograms multiplid with a positiv definit matrix are valid vector variograms. The function computes such a variogram function from a formal description. The formula is a sum. Each summand is either a product of a matrix description and a scalar variogram description or only a scalar variogram description. Scalar variogram descriptions are either formal function calls to

• sph(range) for sperical variogram with range range

• exp(range) for an exponential variogram with range range

• gauss(range) for a Gaussian variogram with range range

• gauss(range) for a cardinal sine variogram with (non-effective) range range

• pow(range) for an power variogram with range range

• lin(unit) linear variogram 1 at unit.

• nugget() for adding a nuggeteffect.

alternatively it can be any expression, which will be evaluated in envir and should depende on a dataset of distantce vectrs h.

The matrix description always comes first. It can be R1 for a rank 1 matrix PSD for a Positive Semidefinite matrix or \(S\) for a scalar Sill factor to be multipled with identiy. Or any other construct evaluating to a matrix or a function of some parameters with default values, that if called is evaluated to a positive semidefinit matrix. R1 and PSD can also be written as calls with providing a vector or respectively a matrix providing the parameter.

The variogram is created with default parametervalues. The parameters can later be modified by modifiying the default parameter with assignments like formals(vg)$sPSD1 = parameterPosdefMat(4*diag(5)). We would anyway expect you to fit the model to the data by a command like vgmFit(logratioVariogram(...),CompLinModCoReg(...))

References

What to cite??

See Also

vgram2lrvgram, CompLinModCoReg, vgmFit

Examples

# NOT RUN {
data(juraset)
X <- with(juraset,cbind(X,Y))
comp <- acomp(juraset,c("Cd","Cu","Pb","Co","Cr"))
CompLinModCoReg(~nugget()+sph(0.5)+R1*exp(0.7),comp)
CompLinModCoReg(~nugget()+R1*sph(0.5)+R1*exp(0.7)+(0.3*diag(5))*gauss(0.3),comp)
CompLinModCoReg(~nugget()+R1*sph(0.5)+R1(c(1,2,3,4,5))*exp(0.7),comp)
# }