Package: dsos 0.1.2

dsos: Dataset Shift with Outlier Scores

Test for no adverse shift in two-sample comparison when we have a training set, the reference distribution, and a test set. The approach is flexible and relies on a robust and powerful test statistic, the weighted AUC. Technical details are in Kamulete, V. M. (2021) <arxiv:1908.04000>. Modern notions of outlyingness such as trust scores and prediction uncertainty can be used as the underlying scores for example.

Authors:Vathy M. Kamulete [aut, cre], Royal Bank of Canada [cph]

dsos_0.1.2.tar.gz
dsos_0.1.2.zip(r-4.7)dsos_0.1.2.zip(r-4.6)dsos_0.1.2.zip(r-4.5)
dsos_0.1.2.tgz(r-4.6-any)dsos_0.1.2.tgz(r-4.5-any)
dsos_0.1.2.tar.gz(r-4.7-any)dsos_0.1.2.tar.gz(r-4.6-any)
dsos_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
dsos/json (API)
NEWS

# Install 'dsos' in R:
install.packages('dsos', repos = c('https://vathymut.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/vathymut/dsos/issues

On CRAN:

Conda:

data-driftdata-validationdataset-shiftsdrift-detectionmachine-learningmlopsmodel-monitoringmodel-validationperformance-monitoringstatistical-process-controlstatistical-tests

5.25 score 2 stars 59 scripts 206 downloads 10 exports 26 dependencies

Last updated from:53c8e7bb5e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK127
source / vignettesOK170
linux-release-x86_64OK114
macos-release-arm64OK166
macos-oldrel-arm64OK181
windows-develOK75
windows-releaseOK73
windows-oldrelOK192
wasm-releaseOK127

Exports:as_bfas_pvalueat_from_osat_oobbf_comparebf_from_ospt_from_ospt_oobpt_refitwauc_from_os

Dependencies:clicodetoolscpp11data.tabledigestfarverfuturefuture.applyggplot2globalsgluegtableisobandlabelinglifecyclelistenvparallellyR6RColorBrewerrlangS7scalessimctestvctrsviridisLitewithr

A 10-minute Crash Course

Rendered frommotivation.Rmdusingknitr::rmarkdownon May 23 2026.

Last update: 2023-02-19
Started: 2021-11-21

Acknowledgements

Rendered fromdependencies.Rmdusingknitr::rmarkdownon May 23 2026.

Last update: 2023-02-19
Started: 2021-11-21

Bring Your Own Scores

Rendered fromdiy-score.Rmdusingknitr::rmarkdownon May 23 2026.

Last update: 2023-02-19
Started: 2021-11-21