Control Parameters for Zero-inflated Count Data Regression
zeroinfl.control.Rd
Various parameters that control fitting of zero-inflated regression models
using zeroinfl
.
Usage
zeroinfl.control(method = "BFGS", maxit = 10000, trace = FALSE,
EM = FALSE, start = NULL, ...)
Arguments
- method
characters string specifying the
method
argument passed tooptim
.- maxit
integer specifying the
maxit
argument (maximal number of iterations) passed tooptim
.- trace
logical or integer controlling whether tracing information on the progress of the optimization should be produced (passed to
optim
).- EM
logical. Should starting values be estimated by the EM (expectation maximization) algorithm? See details.
- start
an optional list with elements
"count"
and"zero"
(and potentially"theta"
) containing the coefficients for the corresponding component.- ...
arguments passed to
optim
.
Details
All parameters in zeroinfl
are estimated by maximum likelihood
using optim
with control options set in zeroinfl.control
.
Most arguments are passed on directly to optim
, only trace
is also
used within zeroinfl
and EM
/start
control the choice
of starting values for calling optim
.
Starting values can be supplied, estimated by the EM (expectation maximization)
algorithm, or by glm.fit
(the default). Standard errors are
derived numerically using
the Hessian matrix returned by optim
. To supply starting
values, start
should be a list with elements "count"
and "zero"
and potentially "theta"
(for negative binomial components only) containing
the starting values for the coefficients of the corresponding component of the
model.
Examples
if (FALSE) { # \dontrun{
data("bioChemists", package = "pscl")
## default start values
fm1 <- zeroinfl(art ~ ., data = bioChemists)
## use EM algorithm for start values
fm2 <- zeroinfl(art ~ ., data = bioChemists, EM = TRUE)
## user-supplied start values
fm3 <- zeroinfl(art ~ ., data = bioChemists,
start = list(count = c(0.7, -0.2, 0.1, -0.2, 0, 0), zero = -1.7))
} # }