Practical robust estimators for the imprecise Dirichlet model
Date
2009-01
Authors
Hutter, Marcus
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Publisher
Elsevier
Abstract
Walley’s imprecise Dirichlet model (IDM) for categorical i.i.d. data extends the classical Dirichlet model to a set of priors. It overcomes several fundamental problems which other approaches to uncertainty suffer from. Yet, to be useful in practice, one needs efficient ways for computing the imprecise = robust sets or intervals. The main objective of this work is to derive exact, conservative, and approximate, robust and credible interval estimates under the IDM for a large class of statistical estimators, including the entropy and mutual information.
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Keywords
Imprecise Dirichlet model, Exact, Credible interval estimates, Entropy, Mutual information
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Source
International Journal of Approximate Reasoning
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Journal article
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Open Access
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Creative Commons Attribution Non-Commercial No Derivatives License
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