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? By default the analytical solution is employed.
For details see below.
start
an optional vector with starting values for all parameters (including phi).
fsmaxit
integer specifying maximal number of additional (quasi) Fisher scoring
iterations. For details see below.
fstol
numeric tolerance for convergence in (quasi) Fisher scoring.
For details see below.
...
arguments passed to optim.
Details
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, and start controls
how optim is called.
After the optim maximization, an additional (quasi) Fisher scoring
can be perfomed to further enhance the result or to perform additional bias reduction.
If fsmaxit is greater than zero, this additional optimization is
performed and it converges if the threshold fstol is attained
for the cross-product of the step size.
Starting values can be supplied via start or estimated by
lm.wfit, using the link-transformed response.
Covariances are in general derived analytically. Only if type = "ML" and
hessian = TRUE, they are determined numerically using the Hessian matrix
returned by optim. In the latter case no Fisher scoring iterations are
performed.
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.
Value
A list with the arguments specified.
See Also
betareg
Examples
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)