Geodesic
SOME LIMIT PROPERTIES OF AN APPROXIMATE LEAST SQUARES ESTIMATOR IN A NONLINEAR REGRESSION MODEL WITH CORRELATED NONZERO MEAN ERRORS
Acta mathematica Universitatis Comenianae, Tome 65 (1996) no. 1 
J. Kalicka. SOME LIMIT PROPERTIES OF AN APPROXIMATE LEAST SQUARES ESTIMATOR IN A NONLINEAR REGRESSION MODEL WITH CORRELATED NONZERO MEAN ERRORS. Acta mathematica Universitatis Comenianae, Tome 65 (1996) no. 1. http://geodesic.mathdoc.fr/item/AMUC_1996_65_1_a12/
@article{AMUC_1996_65_1_a12,
     author = {J. Kalicka},
     title = {SOME {LIMIT} {PROPERTIES} {OF} {AN} {APPROXIMATE} {LEAST} {SQUARES} {ESTIMATOR} {IN} {A} {NONLINEAR} {REGRESSION} {MODEL} {WITH} {CORRELATED} {NONZERO} {MEAN} {ERRORS}},
     journal = {Acta mathematica Universitatis Comenianae},
     year = {1996},
     volume = {65},
     number = {1},
     url = {http://geodesic.mathdoc.fr/item/AMUC_1996_65_1_a12/}
}
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Voir la notice de l'article provenant de la source Comenius University

A nonlinear regression model with correlated, normally distributed errors with non zero means is investigated. The limit properties of bias and the mean square error matrix of the approximate least squares estimator of regression parameters are studied.