f0.control

This function returns control arguments for the \(f_0\) update algorithm.
Each argument has a default value, which will be used unless a different
value is provided by the user.

Fits a generalized linear density ratio model (GLDRM).
A GLDRM is a semiparametric generalized linear model.
In contrast to a GLM, which assumes a particular exponential family distribution,
the GLDRM uses a semiparametric likelihood to estimate the reference distribution.
The reference distribution may be any discrete, continuous, or mixed exponential
family distribution. The model parameters, which include both the regression
coefficients and the cdf of the unspecified reference distribution, are estimated
by maximizing a semiparametric likelihood. Regression coefficients are estimated
with no loss of efficiency, i.e. the asymptotic variance is the same as if the
true exponential family distribution were known.
Huang (2014) <doi:10.1080/01621459.2013.824892>.
Huang and Rathouz (2012) <doi:10.1093/biomet/asr075>.
Rathouz and Gao (2008) <doi:10.1093/biostatistics/kxn030>.

Michael Wurm

gldrm

Generalized Linear Density Ratio Models

Paul Rathouz

f0.control function

<dl><dt>eps</dt>
<dd>Convergence threshold. The update has converged when the relative
change in log-likelihood between iterations is less than <code>eps</code>.
absolute change is less than <code>thesh</code>.</dd>
<dt>maxiter</dt>
<dd>Maximum number of iterations allowed.</dd>
<dt>maxhalf</dt>
<dd>Maximum number of half steps allowed per iteration if
log-likelihood does not improve between iterations.</dd>
<dt>maxlogstep</dt>
<dd>Maximum optimization step size allowed on the
<code>log(f0)</code> scale.</dd></dl>

Arguments

Control arguments for f0 update algorithm — f0.control

<dl>

<dt>eps</dt>
<dd>Convergence threshold. The update has converged when the relative
change in log-likelihood between iterations is less than <code>eps</code>.
absolute change is less than <code>thesh</code>.</dd>


<dt>maxiter</dt>
<dd>Maximum number of iterations allowed.</dd>


<dt>maxhalf</dt>
<dd>Maximum number of half steps allowed per iteration if
log-likelihood does not improve between iterations.</dd>


<dt>maxlogstep</dt>
<dd>Maximum optimization step size allowed on the
<code>log(f0)</code> scale.</dd>

</dl>

f0.control: Control arguments for f0 update algorithm

Description

Usage

Value

Arguments