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glmnetcr (version 1.0.2)

Fit a penalized constrained continuation ratio model for predicting an ordinal response

Description

This packages 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. This package uses the glmnet package fitting algorithm.

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Version

Install

install.packages('glmnetcr')

Monthly Downloads

222

Version

1.0.2

License

GPL-2

Maintainer

Kellie J Archer

Last Published

January 3rd, 2014

Functions in glmnetcr (1.0.2)

print.glmnet.cr

Print a glmnet.cr Object
coef.glmnet.cr

Extract All Model Coefficients
glmnet.cr

Fit a Penalized Constrained Continuation Ratio Model Using Lasso or Elasticnet Regularization Via glmnet
fitted.glmnet.cr

AIC, BIC, Predicted Class, and Fitted Probabilities of Class Membership
glmnetcr-package

Penalized Constrained Continuation Ratio Models for Ordinal Response Prediction using glmnet
diabetes

Gene Expression in Normal, Impaired Fasting Glucose, and Type II Diabetic Males
predict.glmnet.cr

AIC, BIC, Predicted Class, and Fitted Probabilities for All Models
cr.backward

Backward Continuation Ratio Restructure Function
cr.forward

Forward Continuation Ratio Restructure Function
select.glmnet.cr

Select Step of Optimal Fitted AIC or BIC CR Model
plot.glmnet.cr

Plots the Regularization Path Computed from glmnet.cr
nonzero.glmnet.cr

Extract Non-Zero Model Coefficients