\HeaderA{k3.linear}{Linear Skewness Estimate}{k3.linear}
\keyword{nonparametric}{k3.linear}
\begin{Description}\relax
Estimates the skewness of a statistic from its empirical influence values.
\end{Description}
\begin{Usage}
\begin{verbatim}
k3.linear(L, strata=NULL)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{L}] Vector of the empirical influence values of a statistic.  These will usually
be calculated by a call to \code{empinf}.

\item[\code{strata}] A numeric vector or factor specifying which observations (and hence which
components of \code{L}) come from which strata.

\end{ldescription}
\end{Arguments}
\begin{Value}
The skewness estimate calculated from \code{L}.
\end{Value}
\begin{References}\relax
Davison, A. C. and Hinkley, D. V. (1997) 
\emph{Bootstrap Methods and Their Application}. Cambridge University Press.
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{empinf}{empinf}}, \code{\LinkA{linear.approx}{linear.approx}}, \code{\LinkA{var.linear}{var.linear}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
#  To estimate the skewness of the ratio of means for the city data.
ratio <- function(d,w)
     sum(d$x * w)/sum(d$u * w)
k3.linear(empinf(data=city,statistic=ratio))
\end{ExampleCode}
\end{Examples}

