Local inconsistency detection using the Kullback–Leibler divergence measure

Using the concept of information loss between two distributions alongside a semi-objectively defined threshold helped distinguish target comparisons with acceptably low inconsistency from those with material inconsistency when statistical tests for inconsistency were inconclusive.

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Publication Details

Journal
Systematic Reviews
Published
2024-10-17
DOI
https://doi.org/10.1186/s13643-024-02680-4
Citations
5
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
Field-Weighted Citation Impact
1.74

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article

Local inconsistency detection using the Kullback–Leibler divergence measure

Loukia M. Spineli
5 citations
Systematic Reviews
Anomaly Detection Techniques and Applications
1.74
article

Local inconsistency detection using the Kullback–Leibler divergence measure

Loukia M. Spineli
article en
5 citations

Abstract

Using the concept of information loss between two distributions alongside a semi-objectively defined threshold helped distinguish target comparisons with acceptably low inconsistency from those with material inconsistency when statistical tests for inconsistency were inconclusive.

Systematic ReviewsVol. 13(1)
Medizinische Hochschule Hannover (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 13%
Anomaly Detection Techniques and Applications
1.74
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Local inconsistency detection using the Kullback–Leibler divergence measure — Loukia M. Spineli · Systematic Reviews (2024) | TGRS Research Map | TGRS