\HeaderA{longley}{Longley's Economic Regression Data}{longley}
\keyword{datasets}{longley}
\begin{Description}\relax
A macroeconomic data set which provides a well-known example for a
highly collinear regression.
\end{Description}
\begin{Usage}
\begin{verbatim}longley\end{verbatim}
\end{Usage}
\begin{Format}\relax
A data frame with 7 economical variables, observed yearly from 1947 to
1962 (\eqn{n=16}{}).
\describe{
\item[GNP.deflator:] GNP implicit price deflator (\eqn{1954=100}{})
\item[GNP:] Gross National Product.
\item[Unemployed:] number of unemployed.
\item[Armed.Forces:] number of people in the armed forces.
\item[Population:] \sQuote{noninstitutionalized} population
\eqn{\ge}{} 14 years of age.
\item[Year:] the year (time).
\item[Employed:] number of people employed.
}

The regression \code{lm(Employed \textasciitilde{} .)} is known to be highly
collinear.
\end{Format}
\begin{Source}\relax
J. W. Longley (1967)
An appraisal of least-squares programs from the point of view of the
user.
\emph{Journal of the American Statistical Association}, \bold{62},
819--841.
\end{Source}
\begin{References}\relax
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988)
\emph{The New S Language}.
Wadsworth \& Brooks/Cole.
\end{References}
\begin{Examples}
\begin{ExampleCode}
require(stats); require(graphics)
## give the data set in the form it is used in S-PLUS:
longley.x <- data.matrix(longley[, 1:6])
longley.y <- longley[, "Employed"]
pairs(longley, main = "longley data")
summary(fm1 <- lm(Employed ~ ., data = longley))
opar <- par(mfrow = c(2, 2), oma = c(0, 0, 1.1, 0),
            mar = c(4.1, 4.1, 2.1, 1.1))
plot(fm1)
par(opar)
\end{ExampleCode}
\end{Examples}

