variograms | R Documentation |
Valid scalar variogram model functions.
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 )
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. |
The univariate variograms are used in the CompLinCoReg as building blocks of multivariate variogram models.
Spherical variogram
Exponential variogram
The Gaussian variogram.
The cardinal sine variogram.
Linear Variogram. Increases over the sill, which is
reached at range
.
The power variogram. Increases over the sill, which is
reached at range
.
The pure nugget effect variogram.
A vector of size NROW(h), giving the variogram values.
K.Gerald v.d. Boogaart http://www.stat.boogaart.de
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
vgram2lrvgram
,
CompLinModCoReg
,
vgmFit
## 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)
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