R-cran-corpcorEfficient estimation of covariance and partial correlation
1.6.10mathΣ=0 Package not present on quarterly.This port was created during this quarter. It will be in the next quarterly branch but not the current one.
Implements a James-Stein-type shrinkage estimator for the covariance
matrix, with separate shrinkage for variances and correlations. 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 and partial variances. The inverse of the covariance
and correlation matrix can be efficiently computed, 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.
math/R-cran-corpcor: New port: Efficient estimation of covariance and partial
correlation
Implements a James-Stein-type shrinkage estimator for the covariance
matrix, with separate shrinkage for variances and correlations. 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 and partial variances. The inverse of the covariance
and correlation matrix can be efficiently computed, 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.
PR: 296812
Approved by: jrm (mentor)
Differential Revision: https://reviews.freebsd.org/D61259
