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% File src/library/stats/man/fligner.test.Rd
% Part of the R package, https://www.R-project.org
% Copyright 1995-2018 R Core Team
% Distributed under GPL 2 or later
\name{fligner.test}
\alias{fligner.test}
\alias{fligner.test.default}
\alias{fligner.test.formula}
\title{Fligner-Killeen Test of Homogeneity of Variances}
\description{
Performs a Fligner-Killeen (median) test of the null that the
variances in each of the groups (samples) are the same.
}
\usage{
fligner.test(x, \dots)
\method{fligner.test}{default}(x, g, \dots)
\method{fligner.test}{formula}(formula, data, subset, na.action, \dots)
}
\arguments{
\item{x}{a numeric vector of data values, or a list of numeric data
vectors.}
\item{g}{a vector or factor object giving the group for the
corresponding elements of \code{x}.
Ignored if \code{x} is a list.}
\item{formula}{a formula of the form \code{lhs ~ rhs} where \code{lhs}
gives the data values and \code{rhs} the corresponding groups.}
\item{data}{an optional matrix or data frame (or similar: see
\code{\link{model.frame}}) containing the variables in the
formula \code{formula}. By default the variables are taken from
\code{environment(formula)}.}
\item{subset}{an optional vector specifying a subset of observations
to be used.}
\item{na.action}{a function which indicates what should happen when
the data contain \code{NA}s. Defaults to
\code{getOption("na.action")}.}
\item{\dots}{further arguments to be passed to or from methods.}
}
\details{
If \code{x} is a list, its elements are taken as the samples to be
compared for homogeneity of variances, and hence have to be numeric
data vectors. In this case, \code{g} is ignored, and one can simply
use \code{fligner.test(x)} to perform the test. If the samples are
not yet contained in a list, use \code{fligner.test(list(x, ...))}.
Otherwise, \code{x} must be a numeric data vector, and \code{g} must
be a vector or factor object of the same length as \code{x} giving the
group for the corresponding elements of \code{x}.
The Fligner-Killeen (median) test has been determined in a simulation
study as one of the many tests for homogeneity of variances which is
most robust against departures from normality, see Conover, Johnson &
Johnson (1981). It is a \eqn{k}-sample simple linear rank which uses
the ranks of the absolute values of the centered samples and weights
\eqn{a(i) = \mathrm{qnorm}((1 + i/(n+1))/2)}{a(i) = qnorm((1 +
i/(n+1))/2)}. The version implemented here uses median centering in
each of the samples (F-K:med \eqn{X^2} in the reference).
}
\value{
A list of class \code{"htest"} containing the following components:
\item{statistic}{the Fligner-Killeen:med \eqn{X^2} test statistic.}
\item{parameter}{the degrees of freedom of the approximate chi-squared
distribution of the test statistic.}
\item{p.value}{the p-value of the test.}
\item{method}{the character string
\code{"Fligner-Killeen test of homogeneity of variances"}.}
\item{data.name}{a character string giving the names of the data.}
}
\references{
William J. Conover, Mark E. Johnson and Myrle M. Johnson (1981).
A comparative study of tests for homogeneity of variances, with
applications to the outer continental shelf bidding data.
\emph{Technometrics}, \bold{23}, 351--361.
\doi{10.2307/1268225}.
}
\seealso{
\code{\link{ansari.test}} and \code{\link{mood.test}} for rank-based
two-sample test for a difference in scale parameters;
\code{\link{var.test}} and \code{\link{bartlett.test}} for parametric
tests for the homogeneity of variances.
}
% FIXME: could use something more interesting here
\examples{
require(graphics)
plot(count ~ spray, data = InsectSprays)
fligner.test(InsectSprays$count, InsectSprays$spray)
fligner.test(count ~ spray, data = InsectSprays)
## Compare this to bartlett.test()
}
\keyword{htest}