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oem: Orthogonalizing EM: Penalized Regression for Big Tall Data
Solves penalized least squares problems for big tall data using the orthogonalizing EM algorithm of Xiong et al. (2016) <doi:10.1080/00401706.2015.1054436>. The main fitting function is oem() and the functions cv.oem() and xval.oem() are for cross validation, the latter being an accelerated cross validation function for linear models. The big.oem() function allows for out of memory fitting. A description of the underlying methods and code interface is described in Huling and Chien (2022) <doi:10.18637/jss.v104.i06>.
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Package details |
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| Author | Bin Dai [aut], Jared Huling [aut, cre] (<https://orcid.org/0000-0003-0670-4845>), Yixuan Qiu [ctb], Gael Guennebaud [cph], Jitse Niesen [cph] |
| Maintainer | Jared Huling <jaredhuling@gmail.com> |
| License | GPL (>= 2) |
| Version | 2.0.11 |
| URL | https://arxiv.org/abs/1801.09661 https://github.com/jaredhuling/oem https://jaredhuling.org/oem/ |
| Package repository | View on CRAN |
| Installation |
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