Dear R user, I want to do sparse principal component analysis (spca). I am using elastic net package for this and spca() and the code is following from the example.
My question is How can I decide the *K =? *and *para=c(7,4,4,1,1,1)) . So, here k=6 i.e the no of Principal Components. and each pcs say , * ** pc1 number of non zero loading is 7 pc2 number of non zero loading is 4 pc3 number of non zero loading is 4 pc4 number of non zero loading is 1 pc5 number of non zero loading is 1 pc6 number of non zero loading is 1 *How can I know in which pc,s how many non zero loadings will be? Any code??? One answer can be cross validation but I did not find in the package. * ** *Thanks for your help* *Code:* library(elasticnet) > out2<-spca(pitprops,*K=6*,type="Gram",sparse="varnum",trace=TRUE,* para=c(7,4,4,1,1,1)) *iterations 10 iterations 20 iterations 30 iterations 40 > out2 Call: spca(x = pitprops, K = 6, para = c(7, 4, 4, 1, 1, 1), type = "Gram", sparse = "varnum", trace = TRUE) 6 sparse PCs Pct. of exp. var. : 28.2 13.9 13.1 7.4 6.8 6.3 Num. of non-zero loadings : 7 4 4 1 1 1 Sparse loadings PC1 PC2 PC3 PC4 PC5 PC6 topdiam -0.477 0.003 0.000 0 0 0 length -0.469 0.000 0.000 0 0 0 moist 0.000 0.785 0.000 0 0 0 testsg 0.000 0.619 0.000 0 0 0 ovensg 0.180 0.000 0.656 0 0 0 ringtop 0.000 0.000 0.589 0 0 0 ringbut -0.290 0.000 0.470 0 0 0 bowmax -0.343 -0.029 -0.048 0 0 0 bowdist -0.414 0.000 0.000 0 0 0 whorls -0.383 0.000 0.000 0 0 0 clear 0.000 0.000 0.000 -1 0 0 knots 0.000 0.000 0.000 0 -1 0 diaknot 0.000 0.000 0.000 0 0 1 > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.