% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/multivariance-functions.R
\name{multivariance.pvalue}
\alias{multivariance.pvalue}
\title{transform multivariance to p-value}
\usage{
multivariance.pvalue(x)
}
\arguments{
\item{x}{value of a normalized \code{\link{multivariance}} scaled by the sample size (i.e., computed with \code{Nscale = TRUE})}
}
\description{
Computes a conservative p-value for the hypothesis of independence for a given multivariance / m-multivariance / total multivariance.
}
\details{
This is based on a distribution-free approach. The p-value is conservative, i.e. it might be much smaller. This is the counterpart to \code{\link{rejection.level}}. For a less conservative approach see \code{\link{resample.pvalue}} or \code{\link{pearson.pvalue}}.

p-values larger than 0.215 might be incorrect, since the distribution-free estimate on which the computation is based only holds up to 0.215.
}
\references{
For the theoretic background see the references given on the main help page of this package: \link{multivariance-package}.
}