Package: cossonet
Title: Sparse Nonparametric Regression for High-Dimensional Data
Version: 1.0
Authors@R: person("Jieun", "Shin", email = "jieunstat@uos.ac.kr", role = c("aut", "cre"))
Description: 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>.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.1
Imports: cosso, survival, stats, MASS, glmnet, graphics
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), usethis (>= 2.1.5),
        devtools
Config/testthat/edition: 3
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2025-03-11 06:00:46 UTC; jieun
Author: Jieun Shin [aut, cre]
Maintainer: Jieun Shin <jieunstat@uos.ac.kr>
Repository: CRAN
Date/Publication: 2025-03-13 12:10:06 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-26 12:26:55 UTC; unix
Archs: cossonet.so.dSYM
