%% $Id: cvsegments.Rd 37 2005-05-15 13:39:40Z bhm $\encoding{latin1}\name{cvsegments}\alias{cvsegments}\title{Generate segments for cross-validation}\description{  The function generates a list of segments for cross-validation.  Random, consecutive and interleaved segments can be produced.}\usage{cvsegments(N, k, length.seg = ceiling(N/k),           type = c("random", "consecutive", "interleaved"))}\arguments{  \item{N}{Integer.  The number of objects in the data set.}  \item{k}{Integer.  The number of segments to return.}  \item{length.seg}{Integer.  The length of the segments.  If    given, it overrides \code{k}.}  \item{type}{One of \code{"random"}, \code{"consecutive"} and    \code{"interleaved"}.  The type of segments to generate.  Default is    \code{"random"}.}}\details{  If \code{length.seg} is specified, it is used to calculate the number of  segments to generate.  Otherwise \code{k} must be specified.  If  \eqn{k*length.seg \ne N}{k*length.seg <> N}, the  \eqn{k*length.seg - N} last segments will contain only  \eqn{length.seg - 1} indices.  If \code{type} is \code{"random"}, the indices are allocated to  segments in random order.  If it is \code{"consecutive"}, the first  segment will contain the first \eqn{length.seg} indices, and so on.  If \code{type} is \code{"interleaved"}, the first segment will contain  the indices \eqn{1, length.seg+1, 2*lenght.seg+1, \ldots,    (k-1)*length.seg+1}, and so on.}\value{  A list of vectors.  Each vector contains the indices for one segment.  The attribute \code{"incomplete"} contains the number of incomplete  segments, and the attribute \code{"type"} contains the type of segments.}\author{Bj鴕n-Helge Mevik and Ron Wehrens}\examples{## Segments for 10-fold randomised cross-validation:cvsegments(100, 10)## Segments with four objects, taken consecutive:cvsegments(60, length.seg = 4, type = "cons")## Incomplete segmentssegs <- cvsegments(50, length.seg = 3)attr(segs, "incomplete")## Leave-one-out cross-validation:cvsegments(100, 100)## Leave-one-out with variable/unknown data set size n:n <- 50cvsegments(n, length.seg = 1)}\keyword{models}