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\name{NOxEmissions}
\alias{NOxEmissions}
\docType{data}
\encoding{utf8}
\title{NOx Air Pollution Data}
\description{
A typical medium sized environmental data set with hourly measurements
of \eqn{NOx} pollution content in the ambient air.
}
\usage{data(NOxEmissions, package="robustbase")}
\format{
A data frame with 8088 observations on the following 4 variables.
\describe{
\item{\code{julday}}{day number, a factor with levels \code{373}
\dots \code{730}, typically with 24 hourly measurements.}
\item{\code{LNOx}}{\eqn{\log} of hourly mean of NOx concentration in
ambient air [ppb] next to a highly frequented motorway.}
\item{\code{LNOxEm}}{\eqn{\log} of hourly sum of NOx emission of
cars on this motorway in arbitrary units.}
\item{\code{sqrtWS}}{Square root of wind speed [m/s].}
}
}
\details{
The original data set had more observations, but with missing values.
Here, all cases with missing values were omitted
(\code{\link{na.omit}(.)}), and then only those were retained that
belonged to days with at least 20 (fully) observed hourly
measurements.
}
\source{
René Locher (at ZHAW, Switzerland).
%% E-mail to R-SIG-robust mailing list, on 2006-04-20.
}
\seealso{another NOx dataset, \code{\link{ambientNOxCH}}.
}
% \references{
% ~~ possibly secondary sources and usages ~~
% }
\examples{
data(NOxEmissions)
plot(LNOx ~ LNOxEm, data = NOxEmissions, cex = 0.25, col = "gray30")
\dontrun{## these take too much time --
## p = 340 ==> already Least Squares is not fast
(lmNOx <- lm(LNOx ~ . ,data = NOxEmissions))
plot(lmNOx) #-> indication of 1 outlier
M.NOx <- MASS::rlm(LNOx ~ . , data = NOxEmissions)
## M-estimation works
## whereas MM-estimation fails:
try(MM.NOx <- MASS::rlm(LNOx ~ . , data = NOxEmissions, method = "MM"))
## namely because S-estimation fails:
try(lts.NOx <- ltsReg(LNOx ~ . , data = NOxEmissions))
try(lmR.NOx <- lmrob (LNOx ~ . , data = NOxEmissions))
}% don't run
}
\keyword{datasets}
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