Package: BAGofT 1.0.0
Jiawei Zhang
BAGofT: A Binary Regression Adaptive Goodness-of-Fit Test (BAGofT)
The BAGofT assesses the goodness-of-fit of binary classifiers. Details can be found in Zhang, Ding and Yang (2021) <arxiv:1911.03063v2>.
Authors:
BAGofT_1.0.0.tar.gz
BAGofT_1.0.0.tar.gz(r-4.5-noble)BAGofT_1.0.0.tar.gz(r-4.4-noble)
BAGofT_1.0.0.tgz(r-4.4-emscripten)BAGofT_1.0.0.tgz(r-4.3-emscripten)
BAGofT.pdf |BAGofT.html✨
BAGofT/json (API)
# Install 'BAGofT' in R: |
install.packages('BAGofT', 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 3 years agofrom:c73a182fb0. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 31 2024 |
R-4.5-linux | OK | Oct 31 2024 |
Exports:BAGofTparRFtestGlmBitestGlmnettestRFtestXGboostVarImp
Dependencies:dcovrandomForestRcppRcppArmadillo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
A Binary Regression Adaptive Goodness-of-fit Test (BAGofT) | BAGofT |
Adaptive partition based on random forests | parRF |
Testing binomial regressions | testGlmBi |
Testing penalized logistic regressions | testGlmnet |
Testing random forests | testRF |
Testing XGboosts | testXGboost |
Variable Importance | VarImp |