method: characters string specifying either that nlminb
is used for optimization or the method argument passed to optim (typically, "BFGS" or "L-BFGS-B").
maxit: integer specifying the maximal number of iterations in the optimization.
hessian: logical. Should the numerical Hessian matrix from the optim output be used for estimation of the covariance matrix? The default (and only option for nlminb) is to use the analytical expected information rather than the numerical Hessian.
trace: logical or integer controlling whether tracing information on the progress of the optimization should be produced?
start: an optional vector with starting values for all parameters.
...: arguments passed to the optimizer.
Details
All parameters in hetglm are estimated by maximum likelihood using either nlminb (default) or optim
with analytical gradients and (by default) analytical expected information. Further control options can be set in hetglm.control, most of which are simply passed on to the corresponding optimizer.
Starting values can be supplied via start or estimated by glm.fit, using the homoscedastic model. Covariances are derived analytically by default. Alternatively, the numerical Hessian matrix returned by optim can be employed, in case this is used for the optimization itself.