Estimation of the parameters of the nonlinear functional model with known error covariance matrix is discussed. Asymptotic properties of the maximum likelihood estimator for the implicit functional model are presented. The approximate bias in the maximum likelihood estimator due to the nonlinearity of the relationship is given and a bias-adjusted estimator is suggested. Numerical and theoretical results support the superiority of the bias-adjusted estimator relative to the maximum likelihood estimator.
Publié le : 1988-03-14
Classification:
Nonlinear implicit relationship,
measurement errors,
asymptotic bias,
maximum likelihood estimator,
bias-adjusted estimator,
62J02,
62F12,
62H12
@article{1176350696,
author = {Amemiya, Yasuo and Fuller, Wayne A.},
title = {Estimation for the Nonlinear Functional Relationship},
journal = {Ann. Statist.},
volume = {16},
number = {1},
year = {1988},
pages = { 147-160},
language = {en},
url = {http://dml.mathdoc.fr/item/1176350696}
}
Amemiya, Yasuo; Fuller, Wayne A. Estimation for the Nonlinear Functional Relationship. Ann. Statist., Tome 16 (1988) no. 1, pp. 147-160. http://gdmltest.u-ga.fr/item/1176350696/