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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