Package: glmnetcr 1.0.6

glmnetcr: Fit a Penalized Constrained Continuation Ratio Model for Predicting an Ordinal Response

Penalized methods are useful for fitting over-parameterized models. This package includes functions for restructuring an ordinal response dataset for fitting continuation ratio models for datasets where the number of covariates exceeds the sample size or when there is collinearity among the covariates. The 'glmnet' fitting algorithm is used to fit the continuation ratio model after data restructuring.

Authors:Kellie J. Archer

glmnetcr_1.0.6.tar.gz
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glmnetcr.pdf |glmnetcr.html✨
glmnetcr/json (API)
NEWS

# Install 'glmnetcr' in R:

install.packages('glmnetcr', repos = c('https://kelliejarcher.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kelliejarcher/glmnetcr/issues

Datasets:

diabetes - Gene Expression in Normal, Impaired Fasting Glucose, and Type II Diabetic Males

On CRAN:

4.61 score 1 packages 27 scripts 324 downloads 10 exports 10 dependencies

Last updated 3 years agofrom:7500a2d333. Checks:6 OK, 3 NOTE. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Mar 04 2025
R-4.5-win	NOTE	Mar 04 2025
R-4.5-mac	NOTE	Mar 04 2025
R-4.5-linux	NOTE	Mar 04 2025
R-4.4-win	OK	Mar 04 2025
R-4.4-mac	OK	Mar 04 2025
R-4.4-linux	OK	Mar 04 2025
R-4.3-win	OK	Mar 04 2025
R-4.3-mac	OK	Mar 04 2025

Exports:coef.glmnetcr cr.backward cr.forward fitted.glmnetcr glmnetcr nonzero.glmnetcr plot.glmnetcr predict.glmnetcr print.glmnetcr select.glmnetcr

Dependencies:codetools foreach glmnet iterators lattice Matrix Rcpp RcppEigen shape survival

glmnetcr: An R Package for Ordinal Response Prediction in High-Dimensional Data Settings

Rendered fromglmnetcr.Rnwusingutils::Sweaveon Mar 04 2025.

Last update: 2022-04-05
Started: 2022-04-05

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Penalized Constrained Continuation Ratio Models for Ordinal Response Prediction using 'glmnet'	glmnetcr-package
Extract All Model Coefficients	coef.glmnetcr
Gene Expression in Normal, Impaired Fasting Glucose, and Type II Diabetic Males	diabetes
AIC, BIC, Predicted Class, and Fitted Probabilities of Class Membership	fitted.glmnetcr
Fit a Penalized Constrained Continuation Ratio Model Using Lasso or Elasticnet Regularization Via 'glmnet'	glmnetcr
Extract Non-Zero Model Coefficients	nonzero.glmnetcr
Plots the Regularization Path Computed	plot.glmnetcr
AIC, BIC, Predicted Class, and Fitted Probabilities for All Models	predict.glmnetcr
Print a 'glmnetcr' Object	print.glmnetcr
Select Step of Optimal Fitted AIC or BIC CR Model	select.glmnetcr