logbin.control: Auxiliary for Controlling logbin Fitting

In mdonoghoe/logbin: Relative Risk Regression Using the Log-Binomial Model

Auxiliary for Controlling logbin Fitting

Description

Auxiliary function for logbin fitting. Typically only used internally by nplbin, but may be used to construct a control argument to that function.

Usage

logbin.control(bound.tol = 1e-06, epsilon = 1e-08, maxit = 10000, trace = 0,
               coeftrace = FALSE)

Arguments

bound.tol	positive tolerance specifying the interior of the parameter space. If the fitted model is more than bound.tol away from the boundary of the parameter space then it is assumed to be in the interior. This can allow the computational method to terminate early if an interior maximum is found. No early termination is attempted if bound.tol = Inf.
epsilon	positive convergence tolerance \epsilon; the estimates are considered to have converged when \sqrt{ \sum (\theta_{old} - \theta_{new})^2} / \sqrt {\sum \theta_{old}^2} < \epsilon, where \theta is the vector of parameter estimates. This should be smaller than bound.tol.
maxit	integer giving the maximum number of iterations (for a given parameterisation in the case of the CEM algorithm).
trace	number indicating level of output that should be produced. >= 1 gives output for each parameterisation, >= 2 gives output at each iteration.
coeftrace	logical indicating whether the coefficient history should be included as a component of the returned value (for method = "em" and method = "cem").

Details

This is used similarly to glm.control. The control argument of logbin is by default passed to the control argument of nplbin.

When trace is greater than zero, calls to cat produce the output. Hence, options(digits = *) can be used to increase the precision.

Value

A list with components named as the arguments.

Author(s)

Mark W. Donoghoe [e-mail]

See Also

glm.control, the equivalent function for glm fitting.

nplbin, the function used to fit logbin models.

Examples

## Variation on example(glm.control) :

evts <- c(18,17,15,20,10,20,25,13,12)
obs <- rep(30,9)
outcome <- gl(3,1,9)
treatment <- gl(3,3)
oo <- options(digits = 12)
logbin.D93X <- logbin(cbind(evts,obs-evts) ~ outcome + treatment, trace = 2, epsilon = 1e-2)
options(oo)
coef(logbin.D93X)

mdonoghoe/logbin documentation built on June 15, 2025, 5:29 a.m.