fligner.test(x, …)# S3 method for default
fligner.test(x, g, …)
# S3 method for formula
fligner.test(formula, data, subset, na.action, …)
x.
Ignored if x is a list.lhs ~ rhs where lhs
gives the data values and rhs the corresponding groups.model.frame) containing the variables in the
formula formula. By default the variables are taken from
environment(formula).NAs. Defaults to
getOption("na.action")."htest" containing the following components:
"Fligner-Killeen test of homogeneity of variances".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
\(a(i) = \mathrm{qnorm}((1 + i/(n+1))/2)\). The version implemented here uses median centering in
each of the samples (F-K:med \(X^2\) in the reference).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.require(graphics)
plot(count ~ spray, data = InsectSprays)
fligner.test(InsectSprays$count, InsectSprays$spray)
fligner.test(count ~ spray, data = InsectSprays)
## Compare this to bartlett.test()
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