Package: wbacon 0.6-2
wbacon: Weighted BACON Algorithms
The BACON algorithms are methods for multivariate outlier nomination (detection) and robust linear regression by Billor, Hadi, and Velleman (2000) <doi:10.1016/S0167-9473(99)00101-2>. The extension to weighted problems is due to Beguin and Hulliger (2008) <https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X200800110616>; see also <doi:10.21105/joss.03238>.
Authors:
wbacon_0.6-2.tar.gz
wbacon_0.6-2.tar.gz(r-4.5-noble)wbacon_0.6-2.tar.gz(r-4.4-noble)
wbacon_0.6-2.tgz(r-4.4-emscripten)wbacon_0.6-2.tgz(r-4.3-emscripten)
wbacon.pdf |wbacon.html✨
wbacon/json (API)
NEWS
# Install 'wbacon' in R: |
install.packages('wbacon', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tobiasschoch/wbacon/issues
- philips - Philips data
Last updated 4 months agofrom:d48024abe6. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 07 2024 |
R-4.5-linux-x86_64 | OK | Dec 07 2024 |
Exports:centerdistanceis_outliermedian_wquantile_wSeparationIndexwBACONwBACON_reg
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Weighted BACON Algorithms for Multivariate Outlier Nomination (Detection) and Robust Linear Regression | wbacon-package wbacon |
Flag Outliers | is_outlier is_outlier.wbaconlm is_outlier.wbaconmv |
Weighted Median | median_w |
Philips data | philips |
Plot Diagnostics for an Object of Class 'wbaconlm' | plot.wbaconlm |
Plot Diagnostics for an Object of Class 'wbaconmv' | plot.wbaconmv SeparationIndex |
Predicted Values Based on the Weighted BACON Linear Regression | predict.wbaconlm |
Weighted Sample Quantiles | quantile_w |
Weighted BACON Algorithm for Multivariate Outlier Detection | center distance print.wbaconmv summary.wbaconmv vcov.wbaconmv wBACON |
Robust Fitting Linear Regression Models by the BACON Algorithm | coef.wbaconlm fitted.wbaconlm print.wbaconlm residuals.wbaconlm summary.wbaconlm vcov.wbaconlm wBACON_reg |