crch.control: Control Options for crch Models

In crch: Censored Regression with Conditional Heteroscedasticity

Control Options for crch Models

Description

Auxiliary function for crch fitting. Specifies a list of values passed to optim.

Usage

crch.control(method = "BFGS", maxit = NULL, hessian = NULL,
  trace = FALSE, start = NULL, dot = "separate",
  lower = -Inf, upper = Inf, ...)

Arguments

method	optimization method passed to optim
maxit	the maximum number of iterations. Default is 5000 except for method="boosting" where the default is 100.
hessian	logical or NULL. If TRUE the numerical Hessian matrix from the optim output is used for estimation of the covariance matrix. If FALSE no covariance matrix is computed. If NULL (the default) the Hessian matrix is computed analytically for dist="gaussian", dist="logistic", and dist="student" with predefined df. For dist="student" without prespecified df, no analytical solution is available and a numerical Hessian matrix is forced.
trace	non-negative integer. If positive, tracing information on the progress of the optimization is produced.
start	initial values for the parameters to be optimized over.
dot	character specifying how to process formula parts with a dot (.) on the right-hand side. This can either be "separate" so that each formula part is expanded separately or "sequential" so that the parts are expanded sequentially conditional on all prior parts. Default is "separate"
lower, upper	bounds on the variables for the "L-BFGS-B" method, or bounds in which to search for method "Brent".
...	additional parameters passed to optim.

Value

A list with components named as the arguments.

See Also

crch, optim

crch documentation built on Sept. 30, 2024, 9:22 a.m.