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\name{print.pvclust}
\alias{print.pvclust}
\title{Print Function for Pvclust Object}
\description{print clustering method and distance measure used in
hierarchical clustering, \eqn{p}-values and related statistics for
a \code{pvclust} object.
}
\usage{
\method{print}{pvclust}(x, which=NULL, digits=3, ...)
}
\arguments{
\item{x}{object of class \code{pvclust}.}
\item{which}{numeric vector which specifies the numbers of edges
(clusters) of which the values are printed. If \code{NULL} is given,
it prints the values of all edges. The default is \code{NULL}.}
\item{digits}{integer indicating the precision to be used in
rounding.}
\item{...}{other parameters used in the function.}
}
\value{this function prints \eqn{p}-values and some related
statistics.
\item{au}{AU (Approximately Unbiased) \eqn{p}-value, which is more
accurate than BP value as unbiased \eqn{p}-value. It is computed by
multiscale bootstrap resampling.}
\item{bp}{BP (Bootstrap Probability) value, which is a simple
statistic computed by bootstrap resampling. This value tends to be
biased as \eqn{p}-value when the absolute value of \code{c}
(explained below) is large.}
\item{se.au, se.bp}{estimated standard errors for \code{au} and
\code{bp}, respectively.}
\item{v, c}{values related to geometric aspects of
hypotheses. \code{v} is signed distance and \code{c} is curvature of
the boundary.}
\item{pchi}{\eqn{p}-values of chi-square test based on asymptotic theory.}
}
\author{Ryota Suzuki \email{ryota.suzuki@is.titech.ac.jp}}
\keyword{print}
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