Package: corpcor 1.6.10

Korbinian Strimmer

corpcor: 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 details of the method are explained in Schafer and Strimmer (2005) <doi:10.2202/1544-6115.1175> and Opgen-Rhein and Strimmer (2007) <doi:10.2202/1544-6115.1252>. 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.

Authors:Juliane Schafer, Rainer Opgen-Rhein, Verena Zuber, Miika Ahdesmaki, A. Pedro Duarte Silva, and Korbinian Strimmer.

corpcor_1.6.10.tar.gz
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corpcor.pdf |corpcor.html✨
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# Install 'corpcor' in R:

install.packages('corpcor', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/strimmerlab/software/issues

29 exports 8.78 score 0 dependencies 282 dependents 24 mentions 908 scripts 28.7k downloads

Last updated 3 years agofrom:a7ca037ced. Checks:OK: 2. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Sep 14 2024
R-4.5-linux	OK	Sep 14 2024

Exports:cor.shrink cor2pcor cov.shrink crossprod.powcor.shrink decompose.cov decompose.invcov estimate.lambda estimate.lambda.var fast.svd invcor.shrink invcov.shrink is.positive.definite make.positive.definite mpower pcor.shrink pcor2cor powcor.shrink pseudoinverse pvar.shrink rank.condition rebuild.cov rebuild.invcov sm.index sm2vec var.shrink vec2sm wt.moments wt.scale wt.var

Dependencies:

Help page	Topics
The corpcor Package	corpcor-package
Compute Partial Correlation from Correlation Matrix - and Vice Versa	cor2pcor pcor2cor
Shrinkage Estimates of Covariance and Correlation	cor.shrink cov.shrink var.shrink
Fast Singular Value Decomposition	fast.svd
Fast Computation of the Inverse of the Covariance and Correlation Matrix	invcor.shrink invcov.shrink
Compute the Power of a Real Symmetric Matrix	mpower
Shrinkage Estimates of Partial Correlation and Partial Variance	pcor.shrink pvar.shrink
Fast Computation of the Power of the Shrinkage Correlation Matrix	crossprod.powcor.shrink powcor.shrink
Pseudoinverse of a Matrix	pseudoinverse
Positive Definiteness of a Matrix, Rank and Condition Number	is.positive.definite make.positive.definite rank.condition
Rebuild and Decompose the (Inverse) Covariance Matrix	decompose.cov decompose.invcov rebuild.cov rebuild.invcov
Estimation of Shrinkage Intensities	estimate.lambda estimate.lambda.var
Some Tools for Handling Symmetric Matrices	sm.index sm2vec vec2sm
Weighted Expectations and Variances	wt.moments wt.scale wt.var

Package: corpcor 1.6.10

corpcor: Efficient Estimation of Covariance and (Partial) Correlation

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