{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T06:04:30Z","timestamp":1762063470592,"version":"build-2065373602"},"reference-count":24,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,8,19]],"date-time":"2022-08-19T00:00:00Z","timestamp":1660867200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>The monitoring of nuclear safeguards measurements consists of verifying the coherence between the operator declarations and the corresponding inspector measurements on the same nuclear items. Significant deviations may be present in the data, as consequence of problems with the operator and\/or inspector measurement systems. However, they could also be the result of data falsification. In both cases, quantitative analysis and statistical outcomes may be negatively affected by their presence unless robust statistical methods are used. This article aims to investigate the benefits deriving from the introduction of robust procedures in the nuclear safeguards context. In particular, we will introduce a robust estimator for the estimation of the uncertainty components of the measurement error model. The analysis will prove the capacity of robust procedures to limit the bias in simulated and empirical contexts to provide more sounding statistical outcomes. For these reasons, the introduction of robust procedures may represent a step forward in the still ongoing development of reliable uncertainty quantification methods for error variance estimation.<\/jats:p>","DOI":"10.3390\/e24081160","type":"journal-article","created":{"date-parts":[[2022,8,21]],"date-time":"2022-08-21T22:23:13Z","timestamp":1661120593000},"page":"1160","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Introducing Robust Statistics in the Uncertainty Quantification of Nuclear Safeguards Measurements"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2749-9142","authenticated-orcid":false,"given":"Andrea","family":"Cerasa","sequence":"first","affiliation":[{"name":"European Commission, Joint Research Centre, Via E. Fermi 2479, 21027 Ispra, VA, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,19]]},"reference":[{"key":"ref_1","first-page":"4","article-title":"Discussion of the IAEA error approach to producing variance estimates for use in material balance evaluation and the international target values, and comparison to metrological definitions of precision","volume":"45","author":"Walsh","year":"2017","journal-title":"J. Nucl. Mater. Manag."},{"key":"ref_2","first-page":"53","article-title":"Ensuring the effectiveness of safeguards through comprehensive uncertainty quantification","volume":"44","author":"Bonner","year":"2016","journal-title":"J. Nucl. Mater. Manag."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1016\/S0969-8043(00)00216-5","article-title":"A study of the effect of measurement error in predictor variables in nondestructive assay","volume":"53","author":"Burr","year":"2000","journal-title":"Appl. Radiat. 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