Package: SIMEXBoost 0.2.0
Bangxu Qiu
SIMEXBoost: Boosting Method for High-Dimensional Error-Prone Data
Implementation of the boosting procedure with the simulation and extrapolation approach to address variable selection and estimation for high-dimensional data subject to measurement error in predictors. It can be used to address generalized linear models (GLM) in Chen (2023) <doi:10.1007/s11222-023-10209-3> and the accelerated failure time (AFT) model in Chen and Qiu (2023) <doi:10.1111/biom.13898>. Some relevant references include Chen and Yi (2021) <doi:10.1111/biom.13331> and Hastie, Tibshirani, and Friedman (2008, ISBN:978-0387848570).
Authors:
SIMEXBoost_0.2.0.tar.gz
SIMEXBoost_0.2.0.tar.gz(r-4.5-noble)SIMEXBoost_0.2.0.tar.gz(r-4.4-noble)
SIMEXBoost_0.2.0.tgz(r-4.4-emscripten)SIMEXBoost_0.2.0.tgz(r-4.3-emscripten)
SIMEXBoost.pdf |SIMEXBoost.html✨
SIMEXBoost/json (API)
# Install 'SIMEXBoost' in R: |
install.packages('SIMEXBoost', 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 1 years agofrom:175d054d5e. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 11 2024 |
R-4.5-linux | OK | Nov 11 2024 |
Exports:Boost_VSEME_DataSIMEXBoost
Dependencies:MASS
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Boosting Method for High-Dimensional Error-Prone Data | SIMEXBoost-package |
Boosting Method for Variable Selection and Estimation | Boost_VSE |
Boosting Method for High-Dimensional Error-Prone Data | ME_Data |
Boosting Method with SIMEX Correction for High-Dimensional Error-Prone Data | SIMEXBoost |