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Broniatowski, M. (2021). Minimum Divergence Estimators, Maximum Likelihood and the Generalized Bootstrap, Entropy, 23(2), 185. Added by: Rucknium (12/03/2022, 04:38) Last edited by: Rucknium (12/03/2022, 04:40) |
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| Resource type: Journal Article DOI: 10.3390/e23020185 ID no. (ISBN etc.): 1099-4300 BibTeX citation key: Broniatowski2021 View all bibliographic details  |
Categories: Not Monero-focused Keywords: Decoy Selection Creators: Broniatowski Collection: Entropy |
Views: 95/2652
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Attachments
entropy-23-00185-v2.pdf  [34/1183]
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URLs http://dx.doi.org/10.3390/e23020185 |
| Abstract |
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This paper states that most commonly used minimum divergence estimators are MLEs for suited generalized bootstrapped sampling schemes. Optimality in the sense of Bahadur for associated tests of fit under such sampling is considered.
Added by: Rucknium |