cossonet: Sparse Nonparametric Regression for High-Dimensional Data
Estimation of sparse nonlinear functions in nonparametric regression using component selection and smoothing. Designed for the analysis of high-dimensional data, the models support various data types, including exponential family models and Cox proportional hazards models. The methodology is based on Lin and Zhang (2006) <doi:10.1214/009053606000000722>.
| Version: | 1.0 |
| Imports: | cosso,survival, stats,MASS,glmnet, graphics |
| Suggests: | knitr,rmarkdown,testthat (≥ 3.0.0),usethis (≥ 2.1.5),devtools |
| Published: | 2025-03-13 |
| DOI: | 10.32614/CRAN.package.cossonet |
| Author: | Jieun Shin [aut, cre] |
| Maintainer: | Jieun Shin <jieunstat at uos.ac.kr> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | cossonet results |
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