vcov.gam: Extract parameter (estimator) covariance matrix from GAM fit
Description
Extracts the Bayesian posterior covariance matrix of the
parameters or frequentist covariance matrix of the parameter estimators
from a fitted gam object.
fitted model object of class gam as produced by gam().
freq
TRUE to return the frequentist covariance matrix of the
parameter estimators, FALSE to return the Bayesian posterior covariance
matrix of the parameters.
dispersion
a value for the dispersion parameter: not normally used.
unconditional
if TRUE (and freq==FALSE) then the Bayesian
smoothing parameter
uncertainty corrected covariance matrix is returned, if available.
...
other arguments, currently ignored.
Value
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.
Details
Basically, just extracts object$Ve or object$Vp from a gamObject.
References
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.
# NOT RUN {require(mgcv)
n <- 100
x <- runif(n)
y <- sin(x*2*pi) + rnorm(n)*.2mod <- gam(y~s(x,bs="cc",k=10),knots=list(x=seq(0,1,length=10)))
diag(vcov(mod))
# }