The relative curvature measures of nonlinearity proposed by Bates and Watts (1980) are extended to an arbitrary subset of the parameters in a normal, nonlinear regression model. In particular, the subset curvatures proposed indicate the validity of linearization-based approximate confidence intervals for single parameters. The derivation produces the original Bates-Watts measures directly from the likelihood function. When the intrinsic curvature is negligible, the Bates-Watts parameter-effects curvature array contains all information necessary to construct curvature measures for parameter subsets.
Publié le : 1986-12-14
Classification:
Confidence regions,
curvature measures,
Fieller-Creasy problem,
least squares,
likelihood,
62J02,
62F25
@article{1176350166,
author = {Cook, R. Dennis and Goldberg, Miriam L.},
title = {Curvatures for Parameter Subsets in Nonlinear Regression},
journal = {Ann. Statist.},
volume = {14},
number = {2},
year = {1986},
pages = { 1399-1418},
language = {en},
url = {http://dml.mathdoc.fr/item/1176350166}
}
Cook, R. Dennis; Goldberg, Miriam L. Curvatures for Parameter Subsets in Nonlinear Regression. Ann. Statist., Tome 14 (1986) no. 2, pp. 1399-1418. http://gdmltest.u-ga.fr/item/1176350166/