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statfidelity  

Audit Statistical Fidelity of AI-Mediated Official Statistics
View on CRAN: Click here


Download and install statfidelity package within the R console
Install from CRAN:
install.packages("statfidelity")

Install from Github:
library("remotes")
install_github("cran/statfidelity")

Install by package version:
library("remotes")
install_version("statfidelity", "0.1.0")



Attach the package and use:
library("statfidelity")
Maintained by
Leila Marvian Mashhad
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-09-03
Latest Update: 2026-09-03
Description:
Provides deterministic tools for auditing whether artificial intelligence systems preserve the numerical, semantic, contextual, temporal, geographic, unit, provenance, revision, transformation, and uncertainty properties of official statistics. Structured reference statistics and machine-generated claims can be compared with non-compensatory critical-error rules, weakest-link and geometric fidelity summaries, provenance graphs, and portable SHA-256 proof bundles. The package also provides bounded connectors for official Eurostat, World Bank, OECD, United Nations SDG, United Kingdom Office for National Statistics, and United States Bureau of Labor Statistics application programming interfaces, plus an extensible HTTPS JSON API registry with session-only API-key support. Prompt perturbation, statistical red-team generation, minimal-pair tests, and starter benchmark data support reproducible evaluation of generative, retrieval-augmented, and agentic statistical systems. An embedded alignment layer maps claim-level controls to relevant activities of the Generic Statistical Business Process Model (GSBPM) 5.2, including Analyse, Disseminate, Evaluate, Quality Management, and Metadata Management. No specific model provider is required.
How to cite:
Leila Marvian Mashhad (2026). statfidelity: Audit Statistical Fidelity of AI-Mediated Official Statistics. R package version 0.1.0, https://cran.r-project.org/web/packages/statfidelity. Accessed 22 Sep. 2026.
Previous versions and publish date:
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