fligner.test

0th

Percentile

Fligner-Killeen Test of Homogeneity of Variances

Performs a Fligner-Killeen (median) test of the null that the variances in each of the groups (samples) are the same.

Keywords
htest
Usage
fligner.test(x, ...)
"fligner.test"(x, g, ...)
"fligner.test"(formula, data, subset, na.action, ...)
Arguments
x
a numeric vector of data values, or a list of numeric data vectors.
g
a vector or factor object giving the group for the corresponding elements of x. Ignored if x is a list.
formula
a formula of the form lhs ~ rhs where lhs gives the data values and rhs the corresponding groups.
data
an optional matrix or data frame (or similar: see model.frame) containing the variables in the formula formula. By default the variables are taken from environment(formula).
subset
an optional vector specifying a subset of observations to be used.
na.action
a function which indicates what should happen when the data contain NAs. Defaults to getOption("na.action").
...
further arguments to be passed to or from methods.
Details

If 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, g is ignored, and one can simply use fligner.test(x) to perform the test. If the samples are not yet contained in a list, use fligner.test(list(x, ...)).

Otherwise, x must be a numeric data vector, and g must be a vector or factor object of the same length as x giving the group for the corresponding elements of 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 $k$-sample simple linear rank which uses the ranks of the absolute values of the centered samples and weights $a(i) = qnorm((1 + i/(n+1))/2)$. The version implemented here uses median centering in each of the samples (F-K:med $X^2$ in the reference).

Value

A list of class "htest" containing the following components:
statistic
the Fligner-Killeen:med $X^2$ test statistic.
parameter
the degrees of freedom of the approximate chi-squared distribution of the test statistic.
p.value
the p-value of the test.
method
the character string "Fligner-Killeen test of homogeneity of variances".
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. Technometrics 23, 351--361.

See Also

ansari.test and mood.test for rank-based two-sample test for a difference in scale parameters; var.test and bartlett.test for parametric tests for the homogeneity of variances.

Aliases
  • fligner.test
  • fligner.test.default
  • fligner.test.formula
Examples
library(stats) require(graphics) plot(count ~ spray, data = InsectSprays) fligner.test(InsectSprays$count, InsectSprays$spray) fligner.test(count ~ spray, data = InsectSprays) ## Compare this to bartlett.test()
Documentation reproduced from package stats, version 3.2.5, License: Part of R 3.2.5

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