A large deviation result for parameter estimators and its application to nonlinear regression analysis
type: Item
instance of: scholarly article
title: A large deviation result for parameter estimators and its application to nonlinear regression analysis
zbMATH Open document ID: 0661.62021
author: Arthur Sieders
author: Kacha Dzhaparidze
published in: The Annals of Statistics
publication date: 1987-01-01T00:00:00Z
review text: The authors generalize the work of \textit{I. A. Ibragimov} and \textit{R. Z. Khas'minskij}, Statistical estimation: Asymptotic theory. (1981; Zbl 0467.62026), and prove a law of large deviation (LLD) for M-estimators. They also apply this LLD to the problem of parametric nonlinear regression when the regression function is continuous and the errors are independent.
Mathematics Subject Classification ID: 62F12
Mathematics Subject Classification ID: 60F10
Mathematics Subject Classification ID: 62J02
zbMATH DE Number: 4080624
zbMATH Keywords: M-estimators
reviewed by: Rasul A. Khan
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1214/aos/1176350491
OpenAlex ID: W2137026954
DOI: 10.1214/AOS/1176350491
description: scientific article; zbMATH DE number 4080624