Summary Method for Covariance/Correlation Models
DESCRIPTION:
Returns a summary of the covariance/correlation models stored in a
fit.models object with virtual class covfm.
USAGE:
summary.covfm(object, distance=F, ...)
REQUIRED ARGUMENTS:
- object
-
a fit.models object with virtual class covfm that contains the fitted
models.
OPTIONAL ARGUMENTS:
- distance
-
if TRUE, the mahalanobis distances are included in the summary.
VALUE:
a summary.lmfm object with the following components:
- mod.names
-
the names of the models in object.
- calls
-
a list containing the call of each model in object.
- covs
-
a matrix with one row for each model in object containing the unique
covariance/correlation estimates.
- centers
-
a matrix with one row for each model in object containing the location
estimates.
- evals
-
a matrix with one row for each model in object containing the eigenvalues
of the estimated covariance/correlation matrix.
- dists
-
if
distance = T
, the mahalanobis distances
calculated using the covariance/location estimate for each model in
object.
SEE ALSO:
,
,
,
.
EXAMPLES:
cov.mle <- cov(stack.dat)
cov.rbb <- covRob(stack.dat)
cov.fm <- fit.models(cov.rb, cov.mle)
cov.sum <- summary(cov.fm)
cov.sum