corpcor: Efficient Estimation of Covariance and (Partial) Correlation
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 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.
Downloads:
Reverse dependencies:
| Reverse depends: |
arf3DS4, BinNor, care, clustrd, EDISON, FRB, FRCC, GeneNet, GLSME, Hotelling, HPbayes, jackstraw, kcirt, leapp, longitudinal, MAVTgsa, mgpd, miRtest, MultiOrd, mvMORPH, mvSLOUCH, OrdNor, penalizedSVM, PoisNor, qtlhot, sda, sideChannelAttack, SMFI5, ttScreening |
| Reverse imports: |
BMhyd, cape, corHMM, list, lymphclon, MCMCglmm, OUwie, parma, pcalg, perARMA, qgraph, r4ss, relaimpo, semPlot, sparsediscrim |
| Reverse suggests: |
FAiR, NMF, picante, subselect |