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:
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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:d3f923c32d. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 04 2024 |
R-4.5-linux | OK | Nov 04 2024 |
Exports:beta.controlf0.controlgldrmgldrm.controlgldrmCIgldrmLRTgldrmPITtheta.control
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Control arguments for beta update algorithm | beta.control |
Control arguments for f0 update algorithm | f0.control |
Fits a generalized linear density ratio model (GLDRM) | gldrm |
Control arguments for 'gldrm' algorithm | gldrm.control |
Confidence intervals for gldrm coefficients | gldrmCI |
Likelihood ratio test for nested models | gldrmLRT |
Confidence intervals for gldrm coefficients | gldrmPIT |
Predict method for a gldrm object | predict.gldrm |
Print summary of gldrm fit | print.gldrm |
Print confidence interval | print.gldrmCI |
Print likelihood ratio test results | print.gldrmLRT |
Control arguments for theta update algorithm | theta.control |