LaMaModel objectComputes the approximate covariance matrix of the estimated parameters coef(object),
as the inverse Hessian of the negative log-likelihood at the estimate.
# S3 method for LaMaModel
vcov(object, ...)covariance matrix with rows and columns named like coef(object)
model object of class "LaMaModel"
additional arguments (not used)
The Hessian is
the exact Hessian obj$he() for models without random effects,
for models with random effects, the Hessian of the Laplace-approximated marginal likelihood
w.r.t. the fixed parameters, by finite differences of obj$gr() (as in sdreport),
for models from qreml, the Hessian of the penalised negative log-likelihood,
including the penalised coefficients. The covariance is then conditional on the estimated smoothing parameters.
If the Hessian is not positive definite, which indicates that the model has not converged, a warning is issued.
coef.LaMaModel