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corpcor (version 1.6.10)

Efficient Estimation of Covariance and (Partial) Correlation

Description

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 Schafer 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 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.

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Version

Install

install.packages('corpcor')

Monthly Downloads

39,120

Version

1.6.10

License

GPL (>= 3)

Last Published

September 16th, 2021

Functions in corpcor (1.6.10)

shrink.intensity

Estimation of Shrinkage Intensities
smtools

Some Tools for Handling Symmetric Matrices
rebuild.cov

Rebuild and Decompose the (Inverse) Covariance Matrix
rank.condition

Positive Definiteness of a Matrix, Rank and Condition Number
wt.scale

Weighted Expectations and Variances
pcor.shrink

Shrinkage Estimates of Partial Correlation and Partial Variance
mpower

Compute the Power of a Real Symmetric Matrix
corpcor-package

The corpcor Package
invcov.shrink

Fast Computation of the Inverse of the Covariance and Correlation Matrix
powcor.shrink

Fast Computation of the Power of the Shrinkage Correlation Matrix
cor2pcor

Compute Partial Correlation from Correlation Matrix -- and Vice Versa
cov.shrink

Shrinkage Estimates of Covariance and Correlation
fast.svd

Fast Singular Value Decomposition
corpcor-internal

Internal corpcor Functions
pseudoinverse

Pseudoinverse of a Matrix