Dgrubbs

pdgrubbs

number of Monte-Carlo replicates. Defaults to <code>10,000</code>.

logical; if TRUE (default), probabilities are P[X &lt;= x]
otherwise, P[X &gt; x].

lower.tail

logical; if TRUE, probabilities p are given as log(p).

log.p

Distribution function for Grubbs D* distribution.

distribution

For one-way layout experiments the one-way ANOVA can
be performed as an omnibus test. All-pairs multiple comparisons
tests (Tukey-Kramer test, Scheffe test, LSD-test)
and many-to-one tests (Dunnett test) for normally distributed
residuals and equal within variance are available. Furthermore,
all-pairs tests (Games-Howell test, Tamhane's T2 test,
Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one
(Tamhane-Dunnett Test) for normally distributed residuals
and heterogeneous variances are provided. Van der Waerden's normal
scores test for omnibus, all-pairs and many-to-one tests is
provided for non-normally distributed residuals and homogeneous
variances. The Kruskal-Wallis, BWS and Anderson-Darling
omnibus test and all-pairs tests
(Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow-
Fligner test) as well as many-to-one (Nemenyi test, Dunn test,
U-test) are given for the analysis of variance by ranks.
Non-parametric trend tests (Jonckheere test, Cuzick test,
Johnson-Mehrotra test, Spearman test) are included.
In addition, a Friedman-test for one-way ANOVA with repeated
measures on ranks (CRBD) and Skillings-Mack test for unbalanced
CRBD is provided with consequent all-pairs tests (Nemenyi test,
Siegel test, Miller test, Conover test, Exact test)
and many-to-one tests (Nemenyi test, Demsar test, Exact test).
A trend can be tested with Pages's test. Durbin's test
for a two-way balanced incomplete block design (BIBD) is given
in this package as well as Gore's test for CRBD with multiple
observations per cell is given.  Outlier tests, Mandel's k- and
h statistic as well as functions for Type I error and Power
analysis as well as generic summary, print and plot methods
are provided.

Dgrubbs: Grubbs D* distribution

Description

Usage

Arguments

Value

References

See Also

Examples