Minimum divergence estimators, maximum likelihood and exponential families
The dual representation formula of the divergence between two distributions in a parametric model is presented. Resulting estimators do not make use of any grouping or smoothing. For smooth divergences they all coincide with the MLE on any regular exponential family.
Gespeichert in:
| Autor*in: |
Broniatowski, Michel [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Umfang: |
7 |
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| Übergeordnetes Werk: |
Enthalten in: Third dose of COVID-19 mRNA vaccine appears to overcome vaccine hyporesponsiveness in patients with cirrhosis - John, Binu V. ELSEVIER, 2022, Amsterdam |
|---|---|
| Übergeordnetes Werk: |
volume:93 ; year:2014 ; pages:27-33 ; extent:7 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.spl.2014.06.014 |
|---|
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| 520 | |a The dual representation formula of the divergence between two distributions in a parametric model is presented. Resulting estimators do not make use of any grouping or smoothing. For smooth divergences they all coincide with the MLE on any regular exponential family. | ||
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The dual representation formula of the divergence between two distributions in a parametric model is presented. Resulting estimators do not make use of any grouping or smoothing. For smooth divergences they all coincide with the MLE on any regular exponential family. |
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The dual representation formula of the divergence between two distributions in a parametric model is presented. Resulting estimators do not make use of any grouping or smoothing. For smooth divergences they all coincide with the MLE on any regular exponential family. |
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The dual representation formula of the divergence between two distributions in a parametric model is presented. Resulting estimators do not make use of any grouping or smoothing. For smooth divergences they all coincide with the MLE on any regular exponential family. |
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