The efficiency of the second-order nonlinear least squares estimator and its extension

Mijeong Kim, Yanyuan Ma

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

We revisit the second-order nonlinear least square estimator proposed in Wang and Leblanc (Anne Inst Stat Math 60:883-900, 2008) and show that the estimator reaches the asymptotic optimality concerning the estimation variability. Using a fully semiparametric approach, we further modify and extend the method to the heteroscedastic error models and propose a semiparametric efficient estimator in this more general setting. Numerical results are provided to support the results and illustrate the finite sample performance of the proposed estimator.

Original languageEnglish (US)
Pages (from-to)751-764
Number of pages14
JournalAnnals of the Institute of Statistical Mathematics
Volume64
Issue number4
DOIs
StatePublished - Aug 1 2012

Fingerprint

Nonlinear Least Squares
Least Squares Estimator
Heteroscedastic Errors
Estimator
Heteroscedastic Model
Asymptotic Optimality
Efficient Estimator
Error Model
Numerical Results

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

Cite this

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The efficiency of the second-order nonlinear least squares estimator and its extension. / Kim, Mijeong; Ma, Yanyuan.

In: Annals of the Institute of Statistical Mathematics, Vol. 64, No. 4, 01.08.2012, p. 751-764.

Research output: Contribution to journalArticle

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