Package: Sshaped 1.1
Yining Chen
Sshaped: Nonparametric, Tuning-Free Estimation of S-Shaped Functions
Estimation of an S-shaped function and its corresponding inflection point via a least squares approach. A sequential mixed primal-dual based algorithm is implemented for the fast computation. Details can be found in Feng et al. (2022) <doi:10.1111/rssb.12481>.
Authors:
Sshaped_1.1.tar.gz
Sshaped_1.1.tar.gz(r-4.5-noble)Sshaped_1.1.tar.gz(r-4.4-noble)
Sshaped_1.1.tgz(r-4.4-emscripten)Sshaped_1.1.tgz(r-4.3-emscripten)
Sshaped.pdf |Sshaped.html✨
Sshaped/json (API)
| # Install 'Sshaped' in R: |
| install.packages('Sshaped', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:058709b930. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 08 2024 |
| R-4.5-linux-x86_64 | NOTE | Nov 08 2024 |
Exports:cvxregplot.sshapedpredict.sshapedsshapedreg
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Nonparametric, Tuning-Free Estimation of S-Shaped Functions | Sshaped-package Sshaped |
| Estimation of an increasing and convex function | cvxreg |
| Plot of a 'sshaped' object | plot.sshaped |
| Predict method for a 'sshaped' fit | predict.sshaped |
| Estimation of an S-shaped function | sshapedreg |
