landmap (version 0.0.13)

fit.vgmModel,formula,data.frame,SpatialPixelsDataFrame-method: Fit variogram using point data

Description

Fit variogram using point data

Usage

# S4 method for formula,data.frame,SpatialPixelsDataFrame
fit.vgmModel(
  formulaString.vgm,
  rmatrix,
  predictionDomain,
  cov.model = "exponential",
  dimensions = list("2D", "3D", "2D+T", "3D+T"),
  lambda = 0.5,
  psiR = NULL,
  subsample = nrow(rmatrix),
  ini.var,
  ini.range,
  fix.psiA = FALSE,
  fix.psiR = FALSE,
  ...
)

Arguments

formulaString.vgm

formula.

rmatrix

data.frame with coordinates and values of covariates.

predictionDomain

SpatialPixelsDataFrame.

cov.model

covariance model type used by the geoR package.

dimensions

optional 2D or 3D dimensions.

lambda

transformation value used by the geoR package.

psiR

range parameter used by the geoR package.

subsample

number of subset of original samples.

ini.var

initial variance (sill) used by the geoR package.

ini.range

initial range parameter used by the geoR package.

fix.psiA

setting used by the geoR package.

fix.psiR

setting used by the geoR package.

...

optional arguments to pass to the geoR package.

Value

Fitted variogram model

Examples

# NOT RUN {
library("geoR")
library(rgdal)
demo(meuse, echo=FALSE)
vgm = fit.vgmModel(zinc~dist, as.data.frame(meuse), meuse.grid["dist"], lambda=1)
plot(variog(vgm$geodata))
lines(vgm$vgm)
# }