Estimation of nonlinear Berkson-type measurement error models

Statistica Sinica

Volumn 13, Issue 4, 2003, Pages 1201-1210

  Wang, Liqun ^a  

^a UNIVERSITY OF MANITOBA   (Canada)

Author keywords

Asymptotic normality; Consistency; Errors in variables; Least squares method; Minimum distance estimator; Moment estimation

Indexed keywords

EID: 0347599225     PISSN: 10170405     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (10)

1. Amemiya, T. (1985). Advanced Econometrics. Basil Blackwell Ltd., Oxford, UK.
2. Berkson, J. (1950). Are there two regressions? J. Amer. Statist. Assoc. 45, 164-180.
3. Carroll, R. J., Ruppert, D. and Stefanski, L. A. (1995). Measurement Error in Nonlinear Models. Chapman and Hall, London.
4. Cheng, C. and Van Ness, J. W. (1999). Statistical Regression with Measurement Error, Arnold, London.
5. Fuller, A. W. (1987). Measurement Error Models. Wiley, New York.
6. Gallant, A. R. (1987). Nonlinear Statistical Model, Wiley, New York.
7. Huwang, L. and Huang, Y. H. S. (2000). On errors-in-variables in polynomial regression - Berkson case. Staist. Sinica 10, 923-936.
8. McFadden, D. (1989). A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration. Econometrica 57, 995-1026.
9. Pakes, A. and Pollard, D. (1989). Simulation and the Asymptotics of Optimization Estimators. Econometrica 57, 1027-1057.
10. Seber, G. A. and Wild, C. J. (1989). Nonlinear Regression. Wiley, New York.