R: Compositional variogram model fitting

vgmFit {compositions} | R Documentation

## Compositional variogram model fitting

### Description

Fits a parametric variogram model to an empirical logratio-Variogram

### Usage

    vgmFit2lrv(emp,vg,...,mode="log",psgn=rep(-1,length(param)),print.level=1)
    vgmFit(emp,vg,...,mode="log",psgn=rep(-1,length(param)),print.level=1)
    vgmGof(p = vgmGetParameters(vg), emp, vg, mode = "log")
    vgmGetParameters(vg,envir=environment(vg))
    vgmSetParameters(vg,p)

### Arguments

`emp` | An empirical logratio-Variogram as e.g. returned by `logratioVariogram`
`vg` | A compositional clr-variogram (or ilt-vagriogram) model function.
`...` | further parameters to `nlm`
`mode` | either "ls" or "log" for selection of either using either least squares or least squares on logarithmic values.
`psgn` | Contains a parameter code for each of the parameters. -1 means the parameter should be used as is. 0 means the parameter is nonnegativ and 1 means the parameter is striktly positiv. This allows to provide parameter limits if the fitting procedure fails.
`print.level` | The print.level of `nlm`. 0 for no printing. 1 for a rough information about the sucess and 2 for step by step printing.
`p` | Is the parameter of the variogram model in linearized form as e.g. returned by `vgmGetParameters`.
`envir` | The environment the default parameters of the model should be evaluated in.

### Details

The function is mainly a wrapper to `nlm` specifying the an objective function for modell fitting, taking the starting values of fitting procedure from the default arguments and writing the results back. Variogram model fitting is more an art than a straight forward procedure. Fitting procedures typically only find a right optimum if reasonable starting parameters are provided. The fit should be visually checked afterwards.
The meaning of `psgn` is subject to change. We will probably provide a more automatic procedure later.
`vgmFit` is a copy of `vgmFit2lrv`, but deprecated. The name will later be used for other functionality.

### Value

`vgmFit2lrv` returns a list of two elements.

`nlm` | The result of `nlm` containing covergence codes.
`vg` | A version of `vg` but with default parameters modified according to the fitting.

`vgmGof` returns a scalar quantifiying the goodness of fit, of a model and an empirical variogram.
`vgmGetParameters` extracts the default values of a variogram model function to a parameter vector. It returns a numeric vector.
`vgmSetParameters` does the inverse operation and modifies the default according to the new values in `p`. It returns `vg` with modifiend default parameter values.

### Author(s)

K.Gerald v.d. Boogaart http://www.stat.boogaart.de

### See Also

`vgram2lrvgram`, `CompLinModCoReg`, `logratioVariogram`

### Examples

    ## Not run:
    data(juraset)
    X <- with(juraset,cbind(X,Y))
    comp <- acomp(juraset,c("Cd","Cu","Pb","Co","Cr"))
    lrv <- logratioVariogram(comp,X,maxdist=1,nbins=10)
    fff <- CompLinModCoReg(~nugget()+sph(0.5)+R1*exp(0.7),comp)
    fit <- vgmFit(lrv,fff)
    fit
    fff(1:3)
    plot(lrv,lrvg=vgram2lrvgram(fit$vg))

    ## End(Not run)

[Package compositions version 1.40-3 Index]