1 Introduction | 1.1 Available methods | 1.2 Assumptions | 1.3 The role of the data analyst | 1.4 Additional information | 2 Multivariate outlier detection | 2.1 Bushfire data | 2.1.1 Data preparation | 2.1.2 Outlier detection | 2.1.3 Diagnostics | 2.2 Philips data | 3 Robust linear regression | 3.1 Model fit | 3.2 Tuning | 3.3 Model diagnostics | References | Notes
Package: wbacon 0.6-3
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_0.6-3.tar.gz
wbacon_0.6-3.zip(r-4.7)wbacon_0.6-3.zip(r-4.6)wbacon_0.6-3.zip(r-4.5)
wbacon_0.6-3.tgz(r-4.6-x86_64)wbacon_0.6-3.tgz(r-4.6-arm64)wbacon_0.6-3.tgz(r-4.5-x86_64)wbacon_0.6-3.tgz(r-4.5-arm64)
wbacon_0.6-3.tar.gz(r-4.7-arm64)wbacon_0.6-3.tar.gz(r-4.7-x86_64)wbacon_0.6-3.tar.gz(r-4.6-arm64)wbacon_0.6-3.tar.gz(r-4.6-x86_64)
wbacon_0.6-3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
wbacon/json (API)
| # Install 'wbacon' in R: |
| install.packages('wbacon', repos = c('https://tobiasschoch.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tobiasschoch/wbacon/issues
Datasets:
- philips - Philips data
outlieroutlier-detectionrobust-regressionstatisticsopenblasopenmp
Last updated from:2ba45d9510. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 131 | ||
| linux-devel-x86_64 | OK | 116 | ||
| source / vignettes | OK | 153 | ||
| linux-release-arm64 | OK | 123 | ||
| linux-release-x86_64 | OK | 124 | ||
| macos-release-arm64 | OK | 151 | ||
| macos-release-x86_64 | OK | 198 | ||
| macos-oldrel-arm64 | OK | 178 | ||
| macos-oldrel-x86_64 | OK | 219 | ||
| windows-devel | OK | 108 | ||
| windows-release | OK | 86 | ||
| windows-oldrel | OK | 85 | ||
| wasm-release | OK | 100 |
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 |
