Dear R users,
I have some environmental variables and I need to find the best combination
of them in order to separate two main groups (coded 1 and 2). I have
performed a discriminant analysis using the stepclass function as a method
for selecting the most relevant environmental variables.
The problem is that this function includes a parameter (start.vars) and my
results change a lot when I change this variable...Oh my God!!! Then, one
possible functionl is not the best for my data...
grupo<-stepclass(GROUP~W1+W2+W3+W4+W5+W6+W7+W8+W9+W10, data=BD,
method="lda", start.vars = "W1", criterion = "AS", direction = "forward")
I have performed a redundancy analysis first, then there is not highly
correlated variables in the variables that I include in the stepclass
function.
Can anybody help me???
Thank you very much
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