autoKrige.cv {automap}R Documentation

Automatic cross-validation

Description

Uses autofitVariogram to fit a variogram model to the data and then calls krige.cv to perform cross-validation.

Usage

autoKrige.cv(formula, 
             input_data, 
             data_variogram = input_data,
             model = c("Sph", "Exp", "Gau", "Mat"), 
             kappa = c(0.05, seq(0.2, 2, 0.1), 5, 10), 
             fix.values = c(NA,NA,NA), 
             verbose = FALSE, 
             GLS.model = NA,
             ...)

Arguments

formula formula that defines the dependent variable as a linear model of independent variables; suppose the dependent variable has name 'z', for ordinary and simple kriging use the formula 'z~1'; for simple kriging also define 'beta' (see below); for universal kriging, suppose 'z' is linearly dependent on 'x' and 'y', use the formula 'z~x+y'.
input_data An object of the SpatialPointsDataFrame-class containing the data to be interpolated.
data_variogram An optional way to provide a different dataset for the building of the variogram.
model List of models that will be tested during automatic variogram fitting.
kappa List of values for the smoothing parameter of the Matern model that will be tested during automatic variogram fitting.
fix.values Can be used to fix a variogram parameter to a certain value. It consists of a list with a length of three. The items describe the fixed value for the nugget, range and sill respectively. Setting the value to NA means that the value is not fixed. Is passed on to autofitVariogram.
verbose logical, if TRUE autoKrige will give extra information on the fitting process
GLS.model If a variogram model is passed on through this parameter a Generalized Least Squares sample variogram is calculated.
... arguments passed to krige.cv

Value

autoKrige.cv returns an object of class autoKrige.cv. This is a list containing one object of class SpatialPointsDataFrame with the results of the cross-validation, see krige.cv for more details. The attribute name is krige.cv_output.

Author(s)

Paul Hiemstra, p.hiemstra@geo.uu.nl

See Also

krige.cv, autofitVariogram, compare.cv

Examples

data(meuse)
coordinates(meuse) = ~x+y
data(meuse.grid)
gridded(meuse.grid) = ~x+y

kr.cv = autoKrige.cv(log(zinc)~1, meuse, model = c("Exp"))
kr_dist.cv = autoKrige.cv(log(zinc)~sqrt(dist), meuse, 
       model = c("Exp"))
kr_dist_ffreq.cv = autoKrige.cv(log(zinc)~sqrt(dist)+ffreq, 
       meuse, model = c("Exp"))

[Package automap version 1.0-0 Index]