Decorrelation Projection Scalable to High Dimensional Data

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Documentation for package ‘decorrelate’ version 0.1.6.4

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

autocorr.mat	Create auto-correlation matrix
averageCorr	Summarize correlation matrix
averageCorrSq	Summarize correlation matrix
cov_transform	Estimate covariance matrix after applying transformation
decorrelate	Decorrelation projection
dmult	Multiply by diagonal matrix
eclairs	Estimate covariance/correlation with low rank and shrinkage
eclairs-class	Class eclairs
eclairs_corMat	Estimate covariance/correlation with low rank and shrinkage
eclairs_sq	Compute eclairs decomp of squared correlation matrix
effVariance	Summarize correlation matrix
fastcca-class	Class fastcca
getCor	Get full covariance/correlation matrix from eclairs
getCor-method	Get full covariance/correlation matrix from eclairs
getCov	Get full covariance/correlation matrix from eclairs
getCov-method	Get full covariance/correlation matrix from eclairs
getShrinkageParams	Estimate shrinkage parameter by empirical Bayes
getWhiteningMatrix	Get whitening matrix
kappa-method	Compute condition number
lm_each_eclairs	Fit linear model on each feature after decorrelating
lm_eclairs	Fit linear model after decorrelating
logDet	Evaluate the log determinant
mahalanobisDistance	Mahalanobis Distance
mult_eclairs	Multiply by eclairs matrix
optimal_SVHT_coef	Optimal Hard Threshold for Singular Values
plot-method	Plot eclairs object
quadForm	Evaluate quadratic form
reform_decomp	Recompute eclairs after dropping features
rmvnorm_eclairs	Draw from multivariate normal and t distributions
sumInverseCorr	Summarize correlation matrix
sv_threshold	Singular value thresholding
tr	Summarize correlation matrix
whiten	Decorrelation projection + eclairs