mv.Csample.test: C Sample Test of Location

In MNM: Multivariate Nonparametric Methods. An Approach Based on Spatial Signs and Ranks

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, ...)

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.

Details

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

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.

Author(s)

Klaus Nordhausen

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")

Example output

Loading required package: ICSNP
Loading required package: mvtnorm
Loading required package: ICS
Loading required package: SpatialNP

	Several samples location test using Hotellings T2

data:  X by g1
Q.2 = 3.0546, df = 6, p-value = 0.802
alternative hypothesis: true location difference between some groups is not equal to c(0,0,0)


	Several samples location test using spatial signs

data:  X by g1
Q.2 = 2.9023, df = 6, p-value = 0.821
alternative hypothesis: true location difference between some groups is not equal to c(0,0,0)


	Several samples location test using spatial ranks

data:  X by g1
Q.2 = 1.3938, df = 6, p-value = 0.9662
alternative hypothesis: true location difference between some groups is not equal to c(0,0,0)


	Several samples location test using spatial ranks

data:  Y by g2
Q.2 = 4.8987, df = 3, p-value = 0.1794
alternative hypothesis: true location difference between some groups is not equal to c(0,0,0)


	Several samples location test using spatial ranks

data:  Y by g2
Q.2 = 4.8987, replications = 1000, p-value = 0.205
alternative hypothesis: true location difference between some groups is not equal to c(0,0,0)

MNM documentation built on May 2, 2019, 5:09 a.m.