I work with Windows, R 2.4.1. I'm a beginner with R!
After doing a Discriminant Function Analysis, I am trying to run manova to
get a measure of significance of my lda results. I want to predict groups 1
through 4 using 78 variables (bad group/var ratio, I know, but I'm just
exploring the possibilities right now). I've tried with a test matrix and I
get my results fine, so I think it might have something to do with the
matrix I'm using (hence, the sample of my matrix I show below). My matrix,
called disperser.mx in my code, looks like:
disperser P5.38 P6.45 P6.55 P6.63 P7.12 P7.42 P8.10 P8.30
P8.88 P9.09 P9.30
3 0.00 1.34 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
2 0.00 0.00 131.56 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
2 0.00 5.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
3 0.00 72.65 103.26 1.09 0.00 0.00 0.00 0.00 0.00
0.00 0.00
2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
2 0.88 0.48 0.89 0.00 0.00 0.16 0.00 0.00 0.00
0.00 0.00
2 0.00 0.00 0.00 0.00 0.00 0.75 0.00 0.00 0.00
0.00 0.00
4 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
2 0.00 0.00 0.00 0.00 0.00 5.41 20.62 0.00 8.13
8.87 8.27
4 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
2 0.00 133.24 0.00 0.73 0.00 0.00 1.34 2.13 0.00
0.00 0.00
1 0.00 11.08 3.16 0.76 0.00 0.00 0.00 0.00 0.00
0.00 0.00
4 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
4 0.82 0.00 0.00 0.00 4.79 0.00 0.00 33.69 0.00
0.00 11.44
2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
4 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
2 0.00 1.81 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
1 0.00 0.00 0.00 0.00 0.00 6.89 0.00 0.00 0.00
0.00 0.00
2 7.26 8.16 1.50 0.00 1.97 1.28 0.00 4.08 0.00
0.00 1.16
4 0.00 0.00 0.00 0.00 0.00 3.13 0.00 0.00 0.00
0.00 0.00
4 0.00 0.00 0.00 0.00 0.00 0.83 0.00 0.00 0.00
0.00 0.00
1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
2 0.00 1.48 0.22 0.00 0.00 0.00 1.80 0.00 0.66
0.47 0.47
1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00
1 0.00 0.00 0.00 0.00 4.78 0.00 0.00 0.00 0.00
0.00 0.00
...with a lot more variables. The code I am writing to get a manova is:
##first, the code for the discriminant function, just in case it has
something to do with the error I get later##
disperser.mx$disperser<- as.factor (disperser.mx$disperser)
disperser.df <- lda(disperser~., data=disperser.mx)
predict(disperser.df)
attach(disperser.mx)
table(disperser, predict(disperser.df)$class) ## so far so good. I get my
discriminant analysis fine
volatileVar <- disperser.mx[c(2:79)] ## these are all the variables that I
want to use
summary (manova(as.matrix(volatileVar)~disperser.mx$disperser),
test='Wilks') ## here is where I get an error that says "Error in
summary.manova(manova(as.matrix(volatileVar) ~ disperser.mx$disperser), :
residuals have rank 23 < 78"
I would appreciate any help you can offer! Silvia.
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