vcov.gam {mgcv}  R Documentation 
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.
Usage
## S3 method for class 'gam'
vcov(object, sandwich=FALSE, freq = FALSE, dispersion = NULL,unconditional=FALSE, ...)
Arguments
object 
fitted model object of class 
sandwich 
compute sandwich estimate of covariance matrix. Currently expensive for discrete bam fits. 
freq 

dispersion 
a value for the dispersion parameter: not normally used. 
unconditional 
if 
... 
other arguments, currently ignored. 
Details
Basically, just extracts object$Ve
, object$Vp
or object$Vc
(if available) from a gamObject
, unless sandwich==TRUE
in which case the sandwich estimate is computed (with or without the squared bias component).
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
.
Author(s)
Henric Nilsson. Maintained by Simon N. Wood simon.wood@rproject.org
References
Wood, S.N. (2017) Generalized Additive Models: An Introductio with R (2nd ed) CRC Press
See Also
Examples
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))