Returns the variance-covariance matrix of the main parameters of
a fitted model object. The “main” parameters of model
correspond to those returned by coef, and typically do
not contain a nuisance scale parameter (sigma).
vcov(object, …)
# S3 method for lm
vcov(object, complete = TRUE, …)
## and also for '[summary.]glm' and 'mlm'
# S3 method for aov
vcov(object, complete = FALSE, …).vcov.aliased(aliased, vc, complete = TRUE)
a fitted model object, typically. Sometimes also a
summary() object of such a fitted model.
for the aov, lm, glm, mlm, and where
applicable summary.lm etc methods: logical indicating if the
full variance-covariance matrix should be returned also in case of
an over-determined system where some coefficients are undefined and
coef(.) contains NAs correspondingly. When
complete = TRUE, vcov() is compatible with
coef() also in this singular case.
additional arguments for method functions. For the
glm method this can be used to pass a
dispersion parameter.
a logical vector typically identical to
is.na(coef(.)) indicating which coefficients are ‘aliased’.
a variance-covariance matrix, typically “incomplete”, i.e., with no rows and columns for aliased coefficients.
A matrix of the estimated covariances between the parameter estimates
in the linear or non-linear predictor of the model. This should have
row and column names corresponding to the parameter names given by the
coef method.
When some coefficients of the (linear) model are undetermined and
hence NA because of linearly dependent terms (or an
“over specified” model), also called
“aliased”, see alias, then since R version 3.5.0,
vcov() (iff complete = TRUE, i.e., by default for
lm etc, but not for aov) contains corresponding rows and
columns of NAs, wherever coef() has always
contained such NAs.
vcov() is a generic function and functions with names beginning
in vcov. will be methods for this function.
Classes with methods for this function include:
lm, mlm, glm, nls,
summary.lm, summary.glm,
negbin, polr, rlm (in package MASS),
multinom (in package nnet)
gls, lme (in package nlme),
coxph and survreg (in package survival).
(vcov() methods for summary objects allow more
efficient and still encapsulated access when both
summary(mod) and vcov(mod) are needed.)
.vcov.aliased() is an auxiliary function useful for
vcov method implementations which have to deal with singular
model fits encoded via NA coefficients: It augments a vcov--matrix
vc by NA rows and columns where needed, i.e., when
some entries of aliased are true and vc is of smaller dimension
than length(aliased).