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.
- sph
Spherical variogram
- exp
Exponential variogram
- gauss
The Gaussian variogram.
- gauss
The cardinal sine variogram.
- lin
Linear Variogram. Increases over the sill, which is reached at
range
.- pow
The power variogram. Increases over the sill, which is reached at
range
.- nugget
The 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)