Extracts the Bayesian posterior covariance matrix of the
parameters or frequentist covariance matrix of the parameter estimators
from a fitted gam
object.
# S3 method for gam
vcov(object, freq = FALSE, dispersion = NULL,unconditional=FALSE, ...)
A matrix corresponding to the estimated frequentist covariance matrix
of the model parameter estimators/coefficients, or the estimated posterior
covariance matrix of the parameters, depending on the argument freq
.
fitted model object of class gam
as produced by gam()
.
TRUE
to return the frequentist covariance matrix of the
parameter estimators, FALSE
to return the Bayesian posterior covariance
matrix of the parameters.
a value for the dispersion parameter: not normally used.
if TRUE
(and freq==FALSE
) then the Bayesian
smoothing parameter
uncertainty corrected covariance matrix is returned, if available.
other arguments, currently ignored.
Henric Nilsson. Maintained by Simon N. Wood simon.wood@r-project.org
Basically, just extracts object$Ve
or object$Vp
from a gamObject
.
Wood, S.N. (2006) On confidence intervals for generalized additive models based on penalized regression splines. Australian and New Zealand Journal of Statistics. 48(4): 445-464.
gam
require(mgcv)
n <- 100
x <- runif(n)
y <- sin(x*2*pi) + rnorm(n)*.2
mod <- gam(y~s(x,bs="cc",k=10),knots=list(x=seq(0,1,length=10)))
diag(vcov(mod))
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