R: Variogram functions

variograms {compositions} | R Documentation

## Variogram functions

### Description

Valid scalar variogram model functions.

### Usage

    vgram.sph( h , nugget = 0, sill = 1, range= 1,... )
    vgram.exp( h , nugget = 0, sill = 1, range= 1,... )
    vgram.gauss( h , nugget = 0, sill = 1, range= 1,... )
    vgram.cardsin( h , nugget = 0, sill = 1, range= 1,... )
    vgram.lin( h , nugget = 0, sill = 1, range= 1,... )
    vgram.pow( h , nugget = 0, sill = 1, range= 1,... )
    vgram.nugget( h , nugget = 1,...,tol=1E-8 )

### Arguments

`h` | a vector providing distances, a matrix of distance vectors in its rows or a data.frame of distance vectors.
`nugget` | The size of the nugget effect (i.e. the limit to 0). At zero itself the value is always 0.
`sill` | The sill (i.e. the limit to infinity)
`range` | The range parameter. I.e. the distance in which sill is reached or if this does not exist, where the value is in some sense nearly the sill.
`...` | not used
`tol` | The distance that is considered as nonzero.

### Details

The univariate variograms are used in the CompLinCoReg as building blocks of multivariate variogram models.

- sphSpherical variogram

- expExponential variogram

- gaussThe Gaussian variogram.

- gaussThe cardinal sine variogram.

- linLinear Variogram. Increases over the sill, which is reached at `range`.

- powThe power variogram. Increases over the sill, which is reached at `range`.

- nuggetThe pure nugget effect variogram.

### Value

A vector of size NROW(h), giving the variogram values.

### Author(s)

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

### References

Cressie, N.C. (1993) Spatial statistics

Tolosana, van den Boogaart, Pawlowsky-Glahn (2009) Estimating and modeling variograms of compositional data with occasional missing variables in R, StatGis09

### 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"))
    lrv <- logratioVariogram(comp,X,maxdist=1,nbins=10)
    plot(lrv)

    ## End(Not run)

[Package compositions version 1.40-5 Index]