MNM (version 1.0-4)

mv.Csample.test: C Sample Test of Location

Description

Several samples location tests using different scores.

Usage

mv.Csample.test(X, g, score = "identity", stand = "outer", 
                method = "approximation", n.simu = 1000, 
                na.action = na.fail, ...)

Value

A list with class 'htest' containing the following components:

statistic

the value of the test statistic.

parameter

the degrees of freedom for the test statistic or the number of replications in the simulation.

p.value

the p-value for the test.

null.value

the specified hypothesized value of the location.

alternative

a character string with the value 'two.sided'.

method

a character string indicating what type of test was performed.

data.name

a character string giving the name of the data set and of the grouping vector.

Arguments

X

a numeric data frame or matrix of response values.

g

a factor with at least two levels.

score

the score to be used. Possible choices are identity, sign and rank.

stand

the standardization method used. Possible choices are outer and inner.

method

method for the computation of the p-value for the spatial sign and spatial signed-rank tests. Possible choices are approximation and permutation.

n.simu

number of simulated sign changes if method="permutation".

na.action

a function which indicates what should happen when the data contain 'NA's. Default is to fail.

...

arguments that can be passed on to functions used for the estimation of the spatial signs and spatial ranks.

Author

Klaus Nordhausen

Details

This implements the location tests based on identity, sign or rank scores as described in chapter 11 of the MNM book.

References

Oja, H. (2010), Multivariate Nonparametric Methods with R, Springer.

Nordhausen, K. and Oja, H. (2011), Multivariate L1 Methods: The Package MNM, Journal of Statistical Software, 43, 1-28.

See Also

spatial.sign, spatial.rank, HotellingsT2

Examples

X <- rmvt(150,diag(1,3))
g1 <- gl(3,50)
mv.Csample.test(X, g1)
mv.Csample.test(X, g1, score = "s")
mv.Csample.test(X, g1, score = "r")

Y <- rbind(rmvnorm(40,c(0,0,0)), rmvnorm(60,c(0,0,0.4)))
g2 <- factor(rep(1:2, c(40, 60)))
mv.Csample.test(Y, g2, score = "r")
mv.Csample.test(Y, g2, score = "r", method="p")