View source: R/gstatCompatibility.R
as.variogramModel | R Documentation |
Convert a linear model of coregionalisation to the format of package gstat. See gstat::vgm()
for details.
as.variogramModel(m, ...)
## Default S3 method:
as.variogramModel(m, ...)
## S3 method for class 'gmCgram'
as.variogramModel(m, ...)
## S3 method for class 'LMCAnisCompo'
as.variogramModel(m, V = NULL, prefix = NULL, ensurePSD = TRUE, ...)
## S3 method for class 'CompLinModCoReg'
as.variogramModel(m, V = "alr", prefix = NULL, ensurePSD = TRUE, ...)
m |
variogram model |
... |
further arguments for generic functionality |
V |
eventually, specification of the logratio representation to use for compositional data (one of: a matrix of log-contrasts to use, or else one of the strings "alr", "clr" or "ilr") |
prefix |
optional, name prefix for the generated variables if a transformation is used |
ensurePSD |
logical, should positive-definiteness be enforced? defaults to TRUE, which may produce several scary looking but mostly danger-free warnings |
The LMC model specified in the format of package gstat, i.e. as the result
of using gstat::vgm()
default
: Convert an LMC variogram model to gstat format
gmCgram
: Convert an LMC variogram model to gstat format
LMCAnisCompo
: Convert an LMC variogram model to gstat format
CompLinModCoReg
: Convert an LMC variogram model to gstat format
data("jura", package = "gstat")
X = jura.pred[,1:2]
Zc = compositions::acomp(jura.pred[,7:13])
lrmd = compositions::CompLinModCoReg(formula=~nugget()+sph(1.5), comp=Zc)
as.variogramModel(lrmd, V="alr")
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