[R] test for equality of two data sets with multidimensional variables

[Petr Pikal]

Hi

searching in CRAN homepage for hotelling gave me this response

Thanks everyone for your help on this question. I solved the 
problem by 
writing a procedure to calculate Hotelling's T^2 for a one-sample, 
multivariate t-test. Here's how it looks, perhaps it will be useful to 
others. 


data <- cbind(rnorm(50, 0.1, .01), rnorm(50,.1,.01), 
rnorm(50,.1,.01)) 
k <- ncol(data) 
n <- nrow(data) 
xbar <- apply(data, 2, mean) 
mubar <- rep(0,k) #hypothesized means are zero 
dbar <- xbar - mubar 
v <- var(data) 
t2 <- n*dbar%*%solve(v)%*%dbar 
F <- (n-k)*t2/((n-1)*k) 
P <- 1-pf(F,k,n-k) 


A previous post by Peter B. Mandeville was very helpful, as well as 
the 
Johnson/Wichern book on multivariate stats. 
-S. Schultz 

and this

cran.r-project.org/doc/packages/agce.pdf - Podobné stránky 

CRAN - Package SharedHT2
SharedHT2: Shared Hotelling T2 test for small sample microarray 
experiments ...
Derives a Hotelling T2 statistic having an F-distribution using an 
empirical ...

Maybe this is what you want.

HTH
Petr





On 21 Jun 2005 at 13:00, wu sz wrote:

> Hello there,
> 
> I have two data sets with 14 variables each, and wish to do the test
> for equality of their covariance matrices and mean vectors. Normally
> these tests should be done by chi square test (box provided) and
> Hotelling's T square test respectively. Which R functions could do
> this kind of test? I just find some functions could do for one
> dimension, but no for multidimension. Some one suggests bartlett.test,
> but it seems just works for one dimension. Do you know which ones
> could do that, or I have to do R programming by myself?
> 
> Thank you,
> Shengzhe
> 
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Petr Pikal
petr.pikal at precheza.cz