varianceTest {fBasics} | R Documentation |
Two sample variance tests
Description
Tests if two series differ in their distributional variance parameter.
Usage
varianceTest(x, y, method = c("varf", "bartlett", "fligner"),
title = NULL, description = NULL)
Arguments
x , y |
numeric vectors of data values. |
method |
a character string naming which test should be applied. |
title |
an optional title string, if not specified the inputs data name is deparsed. |
description |
optional description string, or a vector of character strings. |
Details
The method="varf"
can be used to compare variances of two
normal samples performing an F test. The null hypothesis is that
the ratio of the variances of the populations from which they were
drawn is equal to one.
The method="bartlett"
performs the Bartlett test of the
null hypothesis that the variances in each of the samples are the
same. This fact of equal variances across samples is also called
homogeneity of variances. Note, that Bartlett's test is
sensitive to departures from normality. That is, if the samples
come from non-normal distributions, then Bartlett's test may simply
be testing for non-normality. The Levene test (not yet implemented)
is an alternative to the Bartlett test that is less sensitive to
departures from normality.
The method="fligner"
performs the Fligner-Killeen test of
the null that the variances in each of the two samples are the same.
Value
an object from class fHTEST
Note
Some of the test implementations are selected from R's ctest
package.
Author(s)
R-core team for hypothesis tests implemented from R's
package ctest
.
References
Conover, W. J. (1971); Practical nonparametric statistics, New York: John Wiley & Sons.
Lehmann E.L. (1986); Testing Statistical Hypotheses, John Wiley and Sons, New York.
Examples
## rnorm -
# Generate Series:
x = rnorm(50)
y = rnorm(50)
## varianceTest -
varianceTest(x, y, "varf")
varianceTest(x, y, "bartlett")
varianceTest(x, y, "fligner")