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gldrm
View on CRAN: Click
here
Download and install gldrm package within the R console
Install from CRAN:
install.packages("gldrm")
Install from Github:
library("remotes")
install_github("cran/gldrm") Install by package version:
library("remotes")
install_version("gldrm", "1.6") Attach the package and use:
library("gldrm")
Maintained by
Michael Wurm
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-06-28
Latest Update: 2024-01-24
Description:
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) .
Huang and Rathouz (2012) .
Rathouz and Gao (2008) .
How to cite:
Michael Wurm (2017). gldrm: Generalized Linear Density Ratio Models. R package version 1.6, https://cran.r-project.org/web/packages/gldrm. Accessed 04 Jun. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for gldrm
Functions, R codes and Examples using
the gldrm R package
Some associated functions: beta.control . f0.control . getBeta . getTheta . getf0 . gldrm.control . gldrm . gldrmCI . gldrmFit . gldrmLRT . gldrmPIT . predict.gldrm . print.gldrm . print.gldrmCI . print.gldrmLRT . theta.control .
Some associated R codes: getBeta.R . getTheta.R . getf0.R . gldrm.R . gldrmCI.R . gldrmFit.R . gldrmLRT.R . gldrmPIT.R . predict-gldrm.R . print-gldrm.R . Full gldrm package functions and examples
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