betareg.control {betareg} | R Documentation |
Various parameters that control fitting of beta regression models
using betareg
.
betareg.control(phi = TRUE, method = "BFGS", maxit = 5000, hessian = FALSE, trace = FALSE, start = NULL, ...)
phi |
logical indicating whether the precision parameter
phi should be treated as a full model parameter (TRUE , default)
or as a nuisance parameter. |
method |
characters string specifying the method argument
passed to optim . |
maxit |
integer specifying the maxit argument (maximal number
of iterations) passed to optim . |
trace |
logical or integer controlling whether tracing information on
the progress of the optimization should be produced (passed to optim ). |
hessian |
logical. Should the numerical Hessian matrix from the optim output
be used for estimation of the covariance matrix? If FALSE (the default),
the analytical solution is employed. |
start |
an optional vector with starting values for all parameters (including phi). |
... |
arguments passed to optim . |
All parameters in betareg
are estimated by maximum likelihood
using optim
with control options set in betareg.control
.
Most arguments are passed on directly to optim
, only start
controls
how optim
is called.
Starting values can be supplied via start
or estimated by
lm.wfit
, using the link-transformed response.
Covariances are derived analytically (if hessian = FALSE
, the default) or
numerically using the Hessian matrix returned by optim
.
The main parameters of interest are the coefficients in the linear predictor of the
model and the additional precision parameter phi which can either
be treated as a full model parameter (default) or as a nuisance parameter. In the latter case
the estimation does not change, only the reported information in output from print
,
summary
, or coef
(among others) will be different. See also examples.
A list with the arguments specified.
data("GasolineYield", package = "betareg") ## regression with phi as full model parameter gy1 <- betareg(yield ~ batch + temp, data = GasolineYield) gy1 ## regression with phi as nuisance parameter gy2 <- betareg(yield ~ batch + temp, data = GasolineYield, phi = FALSE) gy2 ## compare reported output coef(gy1) coef(gy2) summary(gy1) summary(gy2)