| 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/dispersion 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/dispersion 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)