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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