ordinalgmifs-package: Ordinal Response Regression for High-Dimensional Data

In ordinalgmifs: Ordinal Regression for High-Dimensional Data

Ordinal Response Regression for High-Dimensional Data

Description

This package provides a function, ordinalgmifs, for fitting cumulative link, adjacent category, forward and backward continuation ratio, and stereotype ordinal response models when the number of parameters exceeds the sample size, using the the generalized monotone incremental forward stagewise method.

Details

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This package contains generic methods (coef, plot, predict, print, summary) that can be invoked for an object fitted using ordinalgmifs.

Author(s)

Kellie J. Archer [aut, cre] (<https://orcid.org/0000-0003-1555-5781>), Jiayi Hou [aut], Qing Zhou [aut], Kyle Ferber [aut], John G. Layne [com, ctr], Amanda Gentry [rev] Kellie J. Archer, Jiayi Hou, Qing Zhou, Kyle Ferber, John G. Layne, Amanda Gentry

Maintainer: Kellie J. Archer <[e-mail]> Kellie J. Archer <[e-mail]>

References

Hastie T., Taylor J., Tibshirani R., and Walther G. (2007) Forward stagewise regression and the monotone lasso. Electronic Journal of Statistics, 1, 1-29.

See Also

See Also ordinalgmifs. For models where no predictor is penalized see vglm

ordinalgmifs documentation built on May 31, 2023, 6:31 p.m.