positive.svd

nsmall.svd

psmall.svd

pvt.powscor

pvt.svar

pvt.get.lambda

pvt.varlambda

pvt.corlambda

pvt.check.w

pvt.usr

print.shrinkage

internal

corpcor-internal

This package implements a James-Stein-type shrinkage
        estimator for the covariance matrix, with separate shrinkage
        for variances and correlations. The details of the method are
        explained in Sch\"afer and Strimmer (2005) and Opgen-Rhein and
        Strimmer (2007).  The approach is both computationally as well
        as statistically very efficient, it is applicable to "small n,
        large p" data, and always returns a positive definite and
        well-conditioned covariance matrix. In addition to inferring
        the covariance matrix the package also provides shrinkage
        estimators for partial correlations, partial variances, and
        regression coefficients.  The inverse of the covariance and
        correlation matrix can be efficiently computed, and as well as
        any arbitrary power of the shrinkage correlation matrix.
        Furthermore, functions are available for fast singular value
        decomposition, for computing the pseudoinverse, and for
        checking the rank and positive definiteness of a matrix.

corpcor-internal: Internal corpcor Functions

Description

Arguments