Description Usage Arguments Value References Examples
View source: R/CorShrinkData.R
Performs adaptive shrinkage of the sample correlations starting from a data matrix (possibly containing NAs).
1 2 3 4 5 |
data |
The samples by features data matrix. May contain NA values. |
sd_boot |
A Boolean variable indicating if the standard errors of the Fisher z-scores should be computed via Bootstrap methods or through asymptotic formulation of the problem. |
type |
character. Either "cor" or "pcor" - depending on whether to use correlation or partial correlation. Default is "cor". |
cor_method |
The method of correlation used. May be "pearson", "spearman" or "kendall" depending on the type of correlation to be used by the user. |
thresh_up |
Upper threshold for correlations. Defaults to 0.99 |
thresh_down |
Lower threshold for correlations. Defaults to -0.99. |
image |
character. options for plotting the original or the corshrink matrix.
If |
tol |
The tolerance chosen to check how far apart the CorShrink matrix is from the nearest positive definite matrix before applying PD completion. |
nboot |
The number of bootstrap samples if |
image.control |
Control parameters for the image when |
report_model |
if TRUE, outputs the full adaptive shrinkage output, else outputs the shrunken vector. Defaults to FALSE. |
maxiter |
The maximum number of iterations run for the adaptive shrinkage EM algorithm. Default is 1000. |
ash.control |
The control parameters for adaptive shrinkage |
Returns an adaptively shrunk version of the sample correlations matrix.
False Discovery Rates: A New Deal. Matthew Stephens bioRxiv 038216; doi: http://dx.doi.org/10.1101/038216
1 2 | data("sample_by_feature_data")
out <- CorShrinkData(sample_by_feature_data, image = "both")
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