Characterizing M-estimators
We characterize the full classes of M-estimators for semiparametric models of general functionals by formally connecting the theory of consistent loss functions from forecast evaluation with the theory of M-estimation. This novel characterization result allows us to leverage existing results on loss...
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| Hauptverfasser: | , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
8 May 2023
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| In: |
Biometrika
Year: 2023, Pages: 1-8 |
| ISSN: | 1464-3510 |
| DOI: | 10.1093/biomet/asad026 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1093/biomet/asad026
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| Verfasserangaben: | by Timo Dimitriadis, Tobias Fissler and Johanna Ziegel |
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| 520 | |a We characterize the full classes of M-estimators for semiparametric models of general functionals by formally connecting the theory of consistent loss functions from forecast evaluation with the theory of M-estimation. This novel characterization result allows us to leverage existing results on loss functions known from the literature on forecast evaluation in estimation theory. We exemplify advantageous implications for the fields of robust, efficient, equivariant and Pareto-optimal M-estimation. | ||
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