zerotrunc.control: Control Parameters for Zero-Truncated Count Data Regression

In countreg: Count Data Regression

Control Parameters for Zero-Truncated Count Data Regression

Description

Various parameters that control fitting of zero-truncated count regression models using zerotrunc.

Usage

zerotrunc.control(method = "BFGS", maxit = 10000, start = NULL, ...)

Arguments

method	characters string specifying the method argument passed to optim.
maxit	integer specifying the maxit argument (maximal number of iterations) passed to optim.
start	an optional vector of starting values, see details.
...	arguments passed to optim.

Details

All parameters in zerotrunc are estimated by maximum likelihood using optim with control options set in zerotrunc.control. Most arguments are passed on directly to optim, only start is used to control how optim is called.

Starting values can be supplied via start or estimated by glm.fit (default). Standard errors are derived numerically using the Hessian matrix returned by optim. To supply starting values, start should be a vector with (at least) starting values for the regression coefficients. In case a negative binomial distribution with unknown theta is used, a starting value for theta may be supplied by adding an additional vector element (e.g., start = c(coef, theta)); by default theta = 1 is used as the starting value otherwise.

Value

A list with the arguments specified.

See Also

zerotrunc

Examples

data("CrabSatellites", package = "countreg")

## default start values
zt_nb <- zerotrunc(satellites ~ width + as.numeric(color), data = CrabSatellites,
  subset = satellites > 0, dist = "negbin")

## user-supplied start values and other options
zt_nb2 <- zerotrunc(satellites ~ width + as.numeric(color), data = CrabSatellites,
  subset = satellites > 0, dist = "negbin", start = c(0.5, 0, 0))

countreg documentation built on Dec. 4, 2023, 3:09 a.m.