Package: gldrm 1.6

Michael Wurm

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>.

Authors:Michael Wurm [aut, cre], Paul Rathouz [aut]

gldrm_1.6.tar.gz
gldrm_1.6.tar.gz(r-4.5-noble)gldrm_1.6.tar.gz(r-4.4-noble)
gldrm_1.6.tgz(r-4.4-emscripten)gldrm_1.6.tgz(r-4.3-emscripten)
gldrm.pdf |gldrm.html
gldrm/json (API)

# Install 'gldrm' in R:
install.packages('gldrm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

8 exports 0.00 score 0 dependencies 7 scripts 226 downloads

Last updated 8 months agofrom:d3f923c32d. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 22 2024
R-4.5-linuxOKAug 22 2024

Exports:beta.controlf0.controlgldrmgldrm.controlgldrmCIgldrmLRTgldrmPITtheta.control

Dependencies: