R help - May 2005 - Test on mu with multivariate normal distribution

Dear WizaRds,

I am sorry to bother you with a newbie question, but although I tried to solve
my problem using the various .pdf files (Introduction, help pages etc.), I have
come to a complete stop. Please be so kind as to guide me a little bit along my
way of exploring multivariate analysis in R.

I want to test wether the means-vector mu1 of  X, consisting of the means per
column of that matrix , and mu2, i.e. the means per column of Y,  are
distributed equally  under the assumption of a multivariate normal distribution.
I thought ?simtest? could be the right function to get the p-value, but I fail
to use R correctly. Here is what I tried to do:

f1		<- factor(c("8", "10", "12",
"14"))

X		<- matrix(1:16, ncol=4)
colnames(X)	<-
c("Obj1","Obj2","Obj3","Obj4")
X.frame	<- data.frame(f1,X)

Y		<- matrix(1:12, ncol=4)
colnames(Y)	<-
c("Obj1","Obj2","Obj3","Obj4")
Y.frame	<- data.frame(f1,Y)
XY		<- data.frame(X.frame, Y.frame) # won?t work, because of different nr of
rows

test.stat	<- lm(XY ~ f1)	# ???

# simtest(test.stat, XY, type="Tukey")

creates errors already by just staring at it. I apologize.


Thank you so much for your support,
Telse

"Telse Henschel" <telsehenschel at web.de> writes:
> Dear WizaRds,
> 
> I am sorry to bother you with a newbie question, but although I tried to
solve my problem using the various .pdf files (Introduction, help pages etc.), I
have come to a complete stop. Please be so kind as to guide me a little bit
along my way of exploring multivariate analysis in R.
> 
> I want to test wether the means-vector mu1 of  X, consisting of the means
per column of that matrix , and mu2, i.e. the means per column of Y,  are
distributed equally  under the assumption of a multivariate normal distribution.
I thought ?simtest? could be the right function to get the p-value, but I fail
to use R correctly. Here is what I tried to do:
> 
> f1		<- factor(c("8", "10", "12",
"14"))
> 
> X		<- matrix(1:16, ncol=4)
> colnames(X)	<-
c("Obj1","Obj2","Obj3","Obj4")
> X.frame	<- data.frame(f1,X)
> 
> Y		<- matrix(1:12, ncol=4)
> colnames(Y)	<-
c("Obj1","Obj2","Obj3","Obj4")
> Y.frame	<- data.frame(f1,Y)
> XY		<- data.frame(X.frame, Y.frame) # won?t work, because of different
nr of rows
> 
> test.stat	<- lm(XY ~ f1)	# ???
Try this:

X <- matrix(rnorm(16), ncol=4)
Y <- matrix(rnorm(12), ncol=4)
XY <- rbind(X,Y)
g <- factor(rep(1:2,c(4,3)))
fit1 <- lm(XY ~ g)
fit0 <- lm(XY ~ 1)
anova(fit0,fit1)

(using 1:16 and 1:12 for X and Y gives 

Error in anova.mlmlist(object = fit0, fit1) :
        residuals have rank 1 < 4

)
 
> # simtest(test.stat, XY, type="Tukey")
> 
> creates errors already by just staring at it. I apologize.
> 
> 
> Thank you so much for your support,
> Telse
> 
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-- 
   O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)             FAX: (+45) 35327907