pooledS {rags2ridges} | R Documentation |
Compute the pooled covariance or precision matrix estimate
Description
Compute the pooled covariance or precision matrix estimate from a list
of covariance matrices or precision matrices.
Usage
pooledS(Slist, ns, subset = rep(TRUE, length(ns)), mle = TRUE)
pooledP(Plist, ns, subset = rep(TRUE, length(ns)), mle = TRUE)
Arguments
Slist |
A |
ns |
A |
subset |
|
mle |
|
Plist |
A |
Details
When mle
is FALSE
the given covariance/precision matrices is
assumed to have been computed using the denominator ns[i] - 1
. Hence,
the sum of all ns
minus G
is used a the denominator of the
pooled estimate. Conversely, when mle
is TRUE
the total sum of
the sample sizes ns
is used as the denominator in the pooled estimate.
The function pooledP
is equivalent to a wrapper for pooledS
.
That is, it inverts all the precision matrices in Plist
, applies
pooledS
, and inverts the resulting matrix.
Value
pooledS
returns the pooled covariance matrix, that is a
numeric
matrix with the same size as the elements of Slist
.
Similarly, pooledP
returns the pooled precision matrix, i.e. a
numeric
matrix with the same size as the elements of Plist
.
Author(s)
Anders Ellern Bilgrau, Carel F.W. Peeters <carel.peeters@wur.nl>, Wessel N. van Wieringen
Examples
ns <- c(4, 6, 8)
Slist <- createS(ns, p = 6)
pooledS(Slist, ns)
pooledS(Slist, ns, mle = FALSE)
# Pool the first two classes only, leave out the remaning
pooledS(Slist, ns, subset = c(TRUE, TRUE, FALSE))
pooledS(Slist, ns, subset = ns > 5) # Pool studies with sample size > 5
# Pooled precision matrices
ns <- c(7, 8, 9)
Plist <- lapply(createS(ns, p = 6), solve)
pooledS(Plist, ns)