Lu-Smith Normal Scores Test
Performs the Lu-Smith normal score test
normalScoresTest(x, ...) ## Default S3 method: normalScoresTest(x, g, ...) ## S3 method for class 'formula' normalScoresTest(formula, data, subset, na.action, ...)
x |
a numeric vector of data values, or a list of numeric data vectors. |
... |
further arguments to be passed to or from methods. |
g |
a vector or factor object giving the group for the
corresponding elements of |
formula |
a formula of the form |
data |
an optional matrix or data frame (or similar: see
|
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 |
For one-factorial designs with non-normally distributed
residuals the Lu-Smith normal score test can be performed to test
the H_0: F_1(x) = F_2(x) = … = F_k(x) against
the H_\mathrm{A}: F_i (x) \ne F_j(x) ~ (i \ne j) with at least
one strict inequality. This function is basically a wrapper function to
pNormScore of the package SuppDists.
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.
Lu, H., Smith, P. (1979) Distribution of normal scores statistic for nonparametric one-way analysis of variance. Journal of the American Statistical Association 74, 715–722.
normalScoresTest(count ~ spray, data = InsectSprays)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.