https://github.com/cran/coin
Revision 058ed94367feed3a1f8ca93d1837d226eada4fc9 authored by Torsten Hothorn on 28 November 2016, 12:04:30 UTC, committed by cran-robot on 28 November 2016, 12:04:30 UTC
1 parent b633b8b
Tip revision: 058ed94367feed3a1f8ca93d1837d226eada4fc9 authored by Torsten Hothorn on 28 November 2016, 12:04:30 UTC
version 1.1-3
version 1.1-3
Tip revision: 058ed94
PermutationDistribution-methods.Rd
\name{PermutationDistribution-methods}
\docType{methods}
\alias{dperm}
\alias{dperm-methods}
\alias{dperm,AsymptNullDistribution-method}
\alias{dperm,IndependenceTest-method}
\alias{dperm,NullDistribution-method}
\alias{pperm}
\alias{pperm-methods}
\alias{pperm,AsymptNullDistribution-method}
\alias{pperm,IndependenceTest-method}
\alias{pperm,NullDistribution-method}
\alias{qperm}
\alias{qperm-methods}
\alias{qperm,AsymptNullDistribution-method}
\alias{qperm,IndependenceTest-method}
\alias{qperm,NullDistribution-method}
\alias{rperm}
\alias{rperm-methods}
\alias{rperm,IndependenceTest-method}
\alias{rperm,NullDistribution-method}
\alias{support}
\alias{support-methods}
\alias{support,IndependenceTest-method}
\alias{support,NullDistribution-method}
\title{Computation of the Permutation Distribution}
\description{
Methods for computation of the density function, distribution function,
quantile function, random numbers and support of the permutation distribution.
}
\usage{
\S4method{dperm}{AsymptNullDistribution}(object, x, \dots)
\S4method{dperm}{IndependenceTest}(object, x, \dots)
\S4method{dperm}{NullDistribution}(object, x, \dots)
\S4method{pperm}{AsymptNullDistribution}(object, q, \dots)
\S4method{pperm}{IndependenceTest}(object, q, \dots)
\S4method{pperm}{NullDistribution}(object, q, \dots)
\S4method{qperm}{AsymptNullDistribution}(object, p, \dots)
\S4method{qperm}{IndependenceTest}(object, p, \dots)
\S4method{qperm}{NullDistribution}(object, p, \dots)
\S4method{rperm}{IndependenceTest}(object, n, \dots)
\S4method{rperm}{NullDistribution}(object, n, \dots)
\S4method{support}{IndependenceTest}(object, \dots)
\S4method{support}{NullDistribution}(object, \dots)
}
\arguments{
\item{object}{
an object from which the density function, distribution function, quantile
function, random numbers or support of the permutation distribution can be
computed.
}
\item{x, q}{
a numeric vector, the quantiles for which the density function or
distribution function is computed.
}
\item{p}{
a numeric vector, the probabilities for which the quantile function is
computed.
}
\item{n}{
a numeric vector, the number of observations. If \code{length(n) > 1}, the
length is taken to be the number required.
}
\item{\dots}{
further arguments to be passed to methods.
}
}
\details{
The methods \code{dperm}, \code{pperm}, \code{qperm}, \code{rperm} and
\code{support} compute the density function, distribution function, quantile
function, random deviates and support, respectively, of the permutation
distribution.
}
\value{
The density function, distribution function, quantile function, random
deviates or support of the permutation distribution computed from
\code{object}. A numeric vector.
}
\note{
The density of asymptotic permutation distributions for maximum-type tests or
exact permutation distributions obtained by the split-up algoritm is reported
as \code{NA}. The quantile function of asymptotic permutation distributions
for maximum-type tests cannot be computed for \code{p} less than 0.5, due to
limitations in the \pkg{mvtnorm} package. The support of exact permutation
distributions obtained by the split-up algorithm is reported as \code{NA}.
In versions of \pkg{coin} prior to 1.1-0, the support of asymptotic
permutation distributions was given as an interval containing 99.999 \% of the
probability mass. It is now reported as \code{NA}.
}
\examples{
## Two-sample problem
dta <- data.frame(
y = rnorm(20),
x = gl(2, 10)
)
## Exact Ansari-Bradley test
at <- ansari_test(y ~ x, data = dta, distribution = "exact")
## Support of the exact distribution of the Ansari-Bradley statistic
supp <- support(at)
## Density of the exact distribution of the Ansari-Bradley statistic
dens <- dperm(at, supp)
## Plotting the density
plot(supp, dens, type = "s")
## 95 \% quantile
qperm(at, 0.95)
## One-sided p-value
pperm(at, statistic(at))
## Random number generation
rperm(at, 5)
}
\keyword{methods}
\keyword{htest}
\keyword{distribution}
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