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paretoinfer: Sequential Identification of Approximately Pareto-Optimal Alternatives under Noise

Sequential identification of epsilon-Pareto-optimal alternatives among a finite set with noisy, possibly correlated objectives. Simultaneous anytime-valid confidence sequences for every objective of every alternative (Waudby-Smith and Ramdas, 2024, <doi:10.1093/jrsssb/qkad009>) certify, at any time, which alternatives are epsilon-dominated and which are not, report the estimated frontier, the plausible Pareto set and the certified-dominated set, propose the next alternative to evaluate, and record an auditable result contract.

Version: 0.1.0
Depends: R (≥ 4.1)
Imports: cli (≥ 3.6.0), generics, ggplot2 (≥ 3.5.0), rlang (≥ 1.1.0), seqbench (≥ 0.1.0), stats, tibble (≥ 3.2.0), utils
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-10-24
DOI: 10.32614/CRAN.package.paretoinfer
Author: André Leite ORCID iD [aut, cre], Raydonal Ospina ORCID iD [aut], Cristiano Ferraz ORCID iD [aut]
Maintainer: André Leite <leite at castlab.org>
BugReports: https://github.com/castlaboratory/paretoinfer/issues
License: GPL (≥ 3)
URL: https://castlaboratory.github.io/paretoinfer/, https://github.com/castlaboratory/paretoinfer
NeedsCompilation: no
Language: en-GB
Citation: paretoinfer citation info
Materials: README, NEWS
CRAN checks: paretoinfer results

Documentation:

Reference manual: paretoinfer.html , paretoinfer.pdf
Vignettes: Heterogeneous cost and budgets (source, R code)
Frontier shapes and near-ties (source, R code)
Checking the guarantee and the cost (source, R code)
Get started with paretoinfer (source, R code)

Downloads:

Package source: paretoinfer_0.1.0.tar.gz
Windows binaries: r-devel: paretoinfer_0.1.0.zip, r-release: paretoinfer_0.1.0.zip, r-oldrel: paretoinfer_0.1.0.zip
macOS binaries: r-release (arm64): paretoinfer_0.1.0.tgz, r-oldrel (arm64): paretoinfer_0.1.0.tgz, r-release (x86_64): paretoinfer_0.1.0.tgz, r-oldrel (x86_64): paretoinfer_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.