print.gldrm

Prints fitted coefficients and standard errors, along with a likelihood ratio
test against the null model.

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

print.gldrm function

<dl><dt>x</dt>
<dd>S3 object of class "gldrm", returned from the <code>gldrm</code> function.</dd>
<dt>digits</dt>
<dd>Number of digits for rounding.</dd>
<dt>...</dt>
<dd>Unused. Additional arguments for print method.</dd></dl>

Arguments

Print summary of gldrm fit — print.gldrm

<dl>

<dt>x</dt>
<dd>S3 object of class "gldrm", returned from the <code>gldrm</code> function.</dd>


<dt>digits</dt>
<dd>Number of digits for rounding.</dd>


<dt>...</dt>
<dd>Unused. Additional arguments for print method.</dd>

</dl>

print.gldrm: Print summary of gldrm fit

Description

Usage

Arguments