\Header{bcv}{Biased Cross-Validation for Bandwidth Selection}
\keyword{dplot}{bcv}
\begin{Description}\relax
Uses biased cross-validation to select the bandwidth of a  Gaussian
kernel density estimator.
\end{Description}
\begin{Usage}
\begin{verbatim}
bcv(x, nb = 1000, lower, upper)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] a numeric vector

\item[\code{nb}] number of bins to use.

\item[\code{lower, upper}] Range over which to minimize.  The default is almost always satisfactory.

\end{ldescription}
\end{Arguments}
\begin{Value}
a bandwidth
\end{Value}
\begin{References}\relax
Scott, D. W. (1992)
\emph{Multivariate Density Estimation: Theory, Practice, and Visualization.}
Wiley.

Venables, W. N. and Ripley, B. D. (2002)
\emph{Modern Applied Statistics with S.} Fourth edition.  Springer.
\end{References}
\begin{SeeAlso}\relax
\code{\Link{ucv}}, \code{\Link{width.SJ}}, \code{\Link{density}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
bcv(geyser$duration)
\end{ExampleCode}
\end{Examples}

