Robust Z-Estimators for Semiparametric Moment Condition Models.

divergences moment condition models robustness

Journal

Entropy (Basel, Switzerland)
ISSN: 1099-4300
Titre abrégé: Entropy (Basel)
Pays: Switzerland
ID NLM: 101243874

Informations de publication

Date de publication:
30 Jun 2023
Historique:
received: 08 05 2023
revised: 28 06 2023
accepted: 29 06 2023
medline: 29 7 2023
pubmed: 29 7 2023
entrez: 29 7 2023
Statut: epublish

Résumé

In the present paper, we introduce a class of robust Z-estimators for moment condition models. These new estimators can be seen as robust alternatives for the minimum empirical divergence estimators. By using the multidimensional Huber function, we first define robust estimators of the element that realizes the supremum in the dual form of the divergence. A linear relationship between the influence function of a minimum empirical divergence estimator and the influence function of the estimator of the element that realizes the supremum in the dual form of the divergence led to the idea of defining new Z-estimators for the parameter of the model, by using robust estimators in the dual form of the divergence. The asymptotic properties of the proposed estimators were proven, including here the consistency and their asymptotic normality. Then, the influence functions of the estimators were derived, and their robustness is demonstrated.

Identifiants

pubmed: 37509960
pii: e25071013
doi: 10.3390/e25071013
pmc: PMC10377762
pii:
doi:

Types de publication

Journal Article

Langues

eng

Références

Entropy (Basel). 2020 Mar 31;22(4):
pubmed: 33286173
Entropy (Basel). 2021 Apr 06;23(4):
pubmed: 33917362

Auteurs

Aida Toma (A)

Department of Applied Mathematics, Bucharest University of Economic Studies, 010374 Bucharest, Romania.
"Gheorghe Mihoc-Caius Iacob" Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy, 050711 Bucharest, Romania.

Classifications MeSH