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>
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