Description Usage Arguments Details Value Author(s)
View source: R/GuidedSparseKmeans.S.R2out.R
Selection of Tuning Parameter s in Guided Sparse K-means
1 2 | GuidedSparseKmeans.S.R2out(x, R2.per, K, s, lam, nstart = 20,
maxiter = 15, nperms = 50, silence = F)
|
x |
Gene expression matrix, n*p (rows for subjects and columns for genes). |
R2.per |
R-squared or pseudo R-squared between phenotypic variable and expression value of each gene, a vector. |
K |
Number of clusters. |
s |
The boundary of l1n weights, a vector. |
lam |
The intensity of guidance. |
nstart |
Specify the number of starting point for K-means. |
maxiter |
Maximum number of iteration. |
nperms |
Number of permutation times |
silence |
Output progress or not. |
Select tuning parameter s via permutation in Guided Sparse K-means integrating clinical dataset with gene expression dataset.
A list consisting of
nnonzerows |
number of nonzero weights. |
gaps |
gap statistics. |
segaps |
statard error of gap statistics. |
s |
candidates of s. |
s.best |
the best s with largest gap. |
Lingsong Meng
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