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Multivariate tests for testing the null hypothesis that there is no treatment effect in a randomized complete block design using different scores.
mv.2way.test(x, block, treatment, score = c("identity", "sign", "rank"), stand = c("outer", "inner"), method = c("approximation", "permutation"), n.simu = 1000, eps=1.0e-10, n.iter=10000, na.action = na.fail)
A list with class 'htest' containing the following components:
the value of the test statistic.
the degrees of freedom for the test statistic or the number of replications in the simulation.
the p-value for the test.
the specified null hypothesis value of the location.
a character string with the value 'two.sided'.
a character string indicating what type of test was performed.
a character string giving the name of the data set and of the grouping vector.
a numeric data frame or matrix of response variables.
a factor with at least two levels.
the score to be used. Possible choices are identity, sign and rank.
identity
sign
rank
the standardization method used. Possible choices are outer and inner.
outer
inner
method for the computation of the p-value for the spatial sign and spatial rank tests. Possible choices are approximation and permutation.
approximation
permutation
number of simulated permutations if method="permutation".
method="permutation"
convergence criterion.
maximum number of iterations.
a function which indicates what should happen when the data contain 'NA's. Default is to fail.
Jyrki Mottonen jyrki.mottonen@helsinki.fi
This implements the tests described in chapter 12 of the MNM book.
Oja, H. (2010), Multivariate Nonparametric Methods with R, Springer.
mv.1sample.test, mv.Csample.test , mv.2way.est
mv.1sample.test
mv.Csample.test
mv.2way.est
blocks <- gl(10, 5) treatments <- factor(rep(1:5, 10)) X <- rmvnorm(n = 50, mean = c(1,2,3), sigma = diag(3)) mv.2way.test(X, blocks, treatments, score="r", stand="i", method="a")
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