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\name{salinity}
\alias{salinity}
\docType{data}
\title{Salinity Data}
\description{
This is a data set consisting of measurements of water salinity (i.e.,
its salt concentration) and river discharge taken in North Carolina's
Pamlico Sound; This dataset was listed by Ruppert and Carroll
(1980). In Carrol and Ruppert (1985) the physical background of the
data is described. They indicated that observations 5 and 16
correspond to periods of very heavy discharge and showed that the
discrepant observation 5 was masked by observations 3 and 16, i.e.,
only after deletion of these observations it was possible to identify
the influential observation 5.
This data set is a prime example of the masking effect.
}
\usage{data(salinity)}
\format{
A data frame with 28 observations on the following 4 variables.
\describe{
\item{\code{X1}}{Lagged Salinity}
\item{\code{X2}}{Trend}
\item{\code{X3}}{Discharge}
\item{\code{Y}}{Salinity}
}
}
\source{
P. J. Rousseeuw and A. M. Leroy (1987)
\emph{Robust Regression and Outlier Detection};
Wiley, p.82, table 5.
}
\examples{
data(salinity)
summary(lm.sali <- lm(Y ~ . , data = salinity))
summary(rlm.sali <- MASS::rlm(Y ~ . , data = salinity))
summary(lts.sali <- ltsReg(Y ~ . , data = salinity))
salinity.x <- data.matrix(salinity[, 1:3])
c_sal <- covMcd(salinity.x)
plot(c_sal, "tolEllipsePlot")
}
\keyword{datasets}
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