Dear all,
I am learning the subselect package in R, now I want to use GA to select
some potent variable, but some questions are puzzled.
what i want to resolve is that I have one column dependent y and 219
columns independent x. A total 72 observations is contained in the
dataset. I want to select some variables to fit to y. GA is good method to
do it as many paper said. but they often test the model by some
criteria(i.e. LOO r2 (q2), standard deviaton(sd), etc.). can the "subselect
package" get these index(LOO r2,sd) ?
The example in the subselcet manual:
data(swiss)
genetic(cor(swiss),3,4,popsize=10,nger=5,criterion="Rv") is
just
about matrix X, refer to my data is 72 X 219 matrix. how can I correlate
with dependent y(72 X 1 matrix)? I think whether I can use GA to select
some variable only from X matrix(independent), and then use the best subset
to fit y(dependent) using another algorithm(not containing the subselect
package),and then calculate LOO r2 and sd etc. ?
The last questions is that, these 219 indepents have correlation each
other, need they pre-deal with befor applying GA selection? e.g.remove one
of any two indices with a correlation greater than 0.90.
I send my data to the accessory. it is a csv file. the first column is
dependent (y),and the remaining columns are independent. I want to model a
equation with good statistic result(high LOO r2, low sd). HOw Can do.
Thank you!
Best wishes
Kevin http://old.nabble.com/file/p26276493/mk1.df.csv mk1.df.csv
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