Performs Anderson-Darling k-sample test.
adKSampleTest(x, ...)# S3 method for default
adKSampleTest(x, g, ...)
# S3 method for formula
adKSampleTest(formula, data, subset, na.action, ...)
a numeric vector of data values, or a list of numeric data vectors.
further arguments to be passed to or from methods.
a vector or factor object giving the group for the
corresponding elements of "x".
Ignored with a warning if "x" is a list.
a formula of the form response ~ group where
response gives the data values and group a vector or
factor of the corresponding groups.
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).
an optional vector specifying a subset of observations to be used.
a function which indicates what should happen when
the data contain NAs. Defaults to getOption("na.action").
A list with class "htest" containing the following components:
a character string indicating what type of test was performed.
a character string giving the name(s) of the data.
the estimated quantile of the test statistic.
the p-value for the test.
the parameters of the test statistic, if any.
a character string describing the alternative hypothesis.
the estimates, if any.
the estimate under the null hypothesis, if any.
The null hypothesis, H
This function only evaluates version 1 of the k-sample Anderson-Darling
test (i.e. Eq. 6) of Scholz and Stephens (1987).
The p-values are estimated with the extended empirical function
as implemented in ad.pval of
the package kSamples.
Scholz, F.W., Stephens, M.A. (1987) K-Sample Anderson-Darling Tests. Journal of the American Statistical Association 82, 918--924.
# NOT RUN {
## Hollander & Wolfe (1973), 116.
## Mucociliary efficiency from the rate of removal of dust in normal
## subjects, subjects with obstructive airway disease, and subjects
## with asbestosis.
x <- c(2.9, 3.0, 2.5, 2.6, 3.2) # normal subjects
y <- c(3.8, 2.7, 4.0, 2.4) # with obstructive airway disease
z <- c(2.8, 3.4, 3.7, 2.2, 2.0) # with asbestosis
datf <- data.frame(
g = g <- c(rep("ns", length(x)), rep("oad",
length(y)), rep("a", length(z))),
x = x <- c(x, y, z))
adKSampleTest(x ~ g, datf)
# }
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