The Annals of Statistics

Consistent Estimators in Nonlinear Regression for a Noncompact Parameter Space

G. D. Richardson and B. B. Bhattacharyya

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Abstract

Sufficient conditions are given in order to ensure the existence of a sequence of strongly consistent estimators of unknown parameters in a nonlinear regression model. The primary difference between this and earlier work is in the generality of the parameter space. Indeed, the parameter space is assumed to be any separable, completely regular topological space; in particular, this includes all separable metric spaces.

Article information

Source
Ann. Statist., Volume 14, Number 4 (1986), 1591-1596.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176350179

Digital Object Identifier
doi:10.1214/aos/1176350179

Mathematical Reviews number (MathSciNet)
MR868321

Zentralblatt MATH identifier
0625.62045

JSTOR
links.jstor.org

Subjects
Primary: 62J02: General nonlinear regression
Secondary: 62F12: Asymptotic properties of estimators

Keywords
Nonlinear least squares estimator noncompact space strong consistency Stone-Cech compactification

Citation

Richardson, G. D.; Bhattacharyya, B. B. Consistent Estimators in Nonlinear Regression for a Noncompact Parameter Space. Ann. Statist. 14 (1986), no. 4, 1591--1596. doi:10.1214/aos/1176350179. https://projecteuclid.org/euclid.aos/1176350179


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