| invcov.shrink {corpcor} | R Documentation |
The functions invcov.shrink and invcor.shrink implement an
algorithm to efficiently compute
the inverses of shrinkage estimates of covariance (cov.shrink)
and correlation (cor.shrink).
invcov.shrink(x, lambda, lambda.var, w, verbose=TRUE) invcor.shrink(x, lambda, w, verbose=TRUE)
x |
a data matrix |
lambda |
the correlation shrinkage intensity (range 0-1).
If |
lambda.var |
the variance shrinkage intensity (range 0-1).
If |
w |
optional: weights for each data point - if not specified uniform weights are assumed
( |
verbose |
output status while computing (default: TRUE) |
Both invcov.shrink and invcor.shrink rely on
powcor.shrink. This allows to compute the inverses in
a very efficient fashion (much more efficient than directly inverting
the matrices - see the example).
invcov.shrink returns the inverse of the output from cov.shrink.
invcor.shrink returns the inverse of the output from cor.shrink.
Juliane Sch\"afer and Korbinian Strimmer (http://strimmerlab.org).
Sch\"afer, J., and K. Strimmer. 2005. A shrinkage approach to large-scale covariance estimation and implications for functional genomics. Statist. Appl. Genet. Mol. Biol. 4:32. <DOI:10.2202/1544-6115.1175>
powcor.shrink, cov.shrink, pcor.shrink, cor2pcor
# load corpcor library
library("corpcor")
# generate data matrix
p = 500
n = 10
X = matrix(rnorm(n*p), nrow = n, ncol = p)
lambda = 0.23 # some arbitrary lambda
# slow
system.time(
(W1 = solve(cov.shrink(X, lambda)))
)
# very fast
system.time(
(W2 = invcov.shrink(X, lambda))
)
# no difference
sum((W1-W2)^2)