Hi Since a stepwise procedure for variable selection (as e.g. in SPSS) for a LDA is not implemented in R and anyway I cannot be sure, that all the required assumptions for e.g. a procedure using a statistic based on wilks' lambda, hold (such as normality and variance homogeneity) I would like to ask you, what you would recommend me:
shall I e.g. define a criterion such as the error-rate stemming from a leaving-one-out cross-validation and then write my own procedure of including/removing variables? or what would be the golden standard for such a case (my "case" is that I have 2 groups (n1=30, n2=15, number of potential variables: 37, no equal variance in the two groups)) many thanks cheers christoph -- Christoph Lehmann <[EMAIL PROTECTED]> ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
