Usage
sodc.clust(x, centers, l1 = -1, l2 = -1, cv.num = 5, clus = kmeans, boot.num = 20,
l2.idx = seq(-3, 3, by = 6/20), l1.idx = seq(-3, 3, by = 6/20))
Arguments
x
A numberic dataset matrix.
centers
An integer scalar with the desired number of groups.
l1
L1 penalty parameter. The larger lambda1, the sparser result. if l1==-1, will automatically select optimal lambda1.
l2
L2 penalty parameter. if l2==-1, will automatically select optimal lambda2.
cv.num
The numbers of cross validation iteration for selecting tuning parameter lambda2.
clus
The clustering method applied on SODC component.
boot.num
The numbers of bootstrap iteration for selecting tuning parameter lambda1.
l2.idx
A sequence of index numbers from which one can get a sequence of lambda2 values by calculating 10^l2.idx.
l1.idx
A sequence of index numbers from which one can get a sequence of lambda1 values by calculating 10^l1.idx.