Relative efficiency of maximum likelihood and other estimators in a nonlinear regression model with small measurement errors

Alexander Kukush; Hans Schneeweiss

We compare the asymptotic covariance matrix of the ML estimator in a nonlinear measurement error model to the asymptotic covariance matrices of the CS and SQS estimators studied in Kukush et al (2002). For small measurement error variances they are equal up to the order of the measurement error variance and thus nearly equally efficient. -- Measurement Errors ; Maximum Likelihood ; Efficiency ; Small Error Variance

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Year of publication:	2004
Other Persons:	Kukush, Alexander (contributor) ; Schneeweiß, Hans (contributor)
Publisher:	München : Techn. Univ., Sonderforschungsbereich Statistische Analyse Diskreter Strukturen
Subject:	Schätztheorie \| Estimation theory \| Statistischer Fehler \| Statistical error \| Regressionsanalyse \| Regression analysis \| Nichtlineare Regression \| Nonlinear regression \| Maximum-Likelihood-Schätzung \| Maximum likelihood estimation