Various parameters that control fitting of heteroscedastic binary response models
using hetglm.
hetglm.control(method = "nlminb", maxit = 1000,
hessian = FALSE, trace = FALSE, start = NULL, ...)A list with the processed specified arguments.
characters string specifying either that nlminb
is used for optimization or the method argument passed to
optim (typically, "BFGS" or "L-BFGS-B").
integer specifying the maximal number of iterations in the optimization.
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.
logical or integer controlling whether tracing information on the progress of the optimization should be produced?
an optional vector with starting values for all parameters.
arguments passed to the optimizer.
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.
hetglm