gldrm: Generalized Linear Density Ratio Models

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>.

Version: 1.6
Depends: R (≥ 3.2.2)
Imports: stats (≥ 3.2.2), graphics (≥ 3.2.2)
Suggests: testthat (≥ 1.0.2)
Published: 2024-01-24
DOI: 10.32614/CRAN.package.gldrm
Author: Michael Wurm [aut, cre], Paul Rathouz [aut]
Maintainer: Michael Wurm <wurm at>
License: MIT + file LICENSE
NeedsCompilation: no
CRAN checks: gldrm results


Reference manual: gldrm.pdf


Package source: gldrm_1.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): gldrm_1.6.tgz, r-oldrel (arm64): gldrm_1.6.tgz, r-release (x86_64): gldrm_1.6.tgz, r-oldrel (x86_64): gldrm_1.6.tgz
Old sources: gldrm archive


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