Description Usage Arguments Value See Also Examples
View source: R/other_corr_tests.R
Score impact of each sample on sparse leading eigen-value. Compute correlation using all samples (i.e. C), then compute correlation omitting sample i (i.e. Ci). The score the sample i is based on sparse leading eigen-value of the diffrence between C and Ci.
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Y |
data matrix with samples on rows and variables on columns |
method |
specify which correlation method: "pearson", "kendall" or "spearman" |
rho |
a positive constant such that cor(Y) + diag(rep(rho,p)) is positive definite. |
sumabs |
regularization paramter. Value of 1 gives no regularization, sumabs*sqrt(p) is the upperbound of the L_1 norm of v,controling the sparsity of solution. Must be between 1/sqrt(p) and 1. |
score for each sample measure impact on correlation structure
sle.test
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