swh:1:snp:e520bf41b0e99213acde680a9d87fadac1aee079
Tip revision: e10243fbd4eb0cbeaf518e67fbc5b8ad44889954 authored by Martin Schlather on 12 December 2019, 13:40:13 UTC
version 3.3.7
version 3.3.7
Tip revision: e10243f
soil.Rd
\name{soil}
\docType{data}
\alias{soil}
\title{Soil data of North Bavaria, Germany}
\usage{data(soil)}
\description{
Soil physical and chemical data collected on a field in the
Weissenstaedter Becken, Germany
}
\format{
This data frame contains the following columns:
\describe{
\item{x.coord}{x coordinates given in cm}
\item{y.coord}{y coordinates given in cm}
\item{nr}{number of the samples, which were taken in this order}
\item{moisture}{moisture content [Kg/Kg * 100\%]}
\item{NO3.N}{nitrate nitrogen [mg/Kg]}
\item{Total.N}{total nitrogen [mg/Kg]}
\item{NH4.N}{ammonium nitrogen [mg/Kg]}
\item{DOC}{dissolved organic carbon [mg/Kg]}
\item{N20N}{nitrous oxide [mg/Kg dried substance]}
}
}
\details{
For technical reasons some of the data were obtained as differences
of two measurements (which are not available anymore). Therefore,
some of the data have negative values.
}
\source{
The data were collected by Wolfgang Falk,
Soil Physics Group,
% \url{http://www.geo.uni-bayreuth.de/bodenphysik/Welcome.html},
University of Bayreuth, Germany.
}
\references{
Falk, W. (2000)
\emph{Kleinskalige raeumliche Variabilitaet von Lachgas und bodenchemischen
Parameters [Small Scale Spatial Variability of Nitrous Oxide and
Pedo-Chemical Parameters]},
Master thesis, University of Bayreuth, Germany.
}
\me
\examples{\dontshow{StartExample()} % library("RandomFields")
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
################################################################
## ##
## a geostatistical analysis that demonstrates ##
## features of the package 'RandomFields' ##
## ##
################################################################
data(soil)
str(soil)
soil <- RFspatialPointsDataFrame(
coords = soil[ , c("x.coord", "y.coord")],
data = soil[ , c("moisture", "NO3.N", "Total.N", "NH4.N", "DOC", "N20N")],
RFparams=list(vdim=6, n=1)
)
dta <- soil["moisture"]
\dontshow{if (RFoptions()$internal$examples_red) {
warning("data have been reduced !")
rm(soil) ## muss vorher entfernt werden, sonst funktioniert data(soil)
## nicht sicher
data(soil)
All <- 1:7
soil <- RFspatialPointsDataFrame(
coords = soil[All, c("x.coord", "y.coord")],
data = soil[All, c("moisture", "NO3.N", "Total.N",
"NH4.N", "DOC", "N20N")],
RFparams=list(vdim=6, n=1)
)
dta <- soil["moisture"]
}}
## plot the data first
colour <- rainbow(100)
plot(dta, col=colour)
## fit by eye
gui.model <- RFgui(dta)
\dontshow{if (!interactive()) gui.model <- RMexp()} %ok
## fit by ML
model <- ~1 + RMwhittle(scale=NA, var=NA, nu=NA) + RMnugget(var=NA)
(fit <- RFfit(model, data=dta))
plot(fit, method=c("ml", "plain", "sqrt.nr", "sd.inv"),
model = gui.model, col=1:8)
## Kriging ...
x <- seq(min(dta@coords[, 1]), max(dta@coords[, 1]), l=121)
k <- RFinterpolate(fit, x=x, y=x, data=dta)
plot(x=k, col=colour)
plot(x=k, y=dta, col=colour)
## what is the probability that at no point of the
## grid given by x and y the moisture is greater than 24 percent?
% works well since fit$ml:nugget==0!!!!
cs <- RFsimulate(model=fit@ml, x=x, y=x, data=dta, n=50)
plot(cs, col=colour)
plot(cs, y=dta, col=colour)
Print(mean(apply(as.array(cs) <= 24, 3, all))) ## about 40 percent ...
\dontshow{FinalizeExample()}}
\keyword{datasets}