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dsos (version 0.1.2)

Dataset Shift with Outlier Scores

Description

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) . Modern notions of outlyingness such as trust scores and prediction uncertainty can be used as the underlying scores for example.

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Install

install.packages('dsos')

Monthly Downloads

240

Version

0.1.2

License

GPL (>= 3)

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Maintainer

Vathy M. Kamulete

Last Published

February 19th, 2023

Functions in dsos (0.1.2)

dsos-package

dsos: Dataset Shift with Outlier Scores
print.outlier.bayes

Print Bayesian test for no adverse shift.
wauc_from_os

Weighted AUC from Outlier Scores
pt_oob

Permutation Test With Out-Of-Bag Scores
at_from_os

Asymptotic Test from Outlier Scores
at_oob

Asymptotic Test With Out-Of-Bag Scores
plot.outlier.test

Plot frequentist test for no adverse shift.
pt_refit

Permutation Test By Refitting
as_pvalue

Convert Bayes Factor to P-value
print.outlier.test

Print frequentist test for no adverse shift.
bf_compare

Bayesian and Frequentist Test from Outlier Scores
bf_from_os

Bayesian Test from Outlier Scores
plot.outlier.bayes

Plot Bayesian test for no adverse shift.
as_bf

Convert P-value to Bayes Factor
pt_from_os

Permutation Test from Outlier Scores