The class of nonlinear stochastic regression models includes most
of the linear and nonlinear models used in time series, stochastic control and
stochastic approximation schemes.The consistency of least squares estimators
was established first by Lai.We present another set of sufficient conditions
for consistency, which avoid the use of partial derivatives and are closer in
spirit to the conditions presented by Wu for non-stochastic regression models
with independent errors.
Publié le : 2000-05-14
Classification:
Consistency,
least squares estimator,
martingale,
stochastic regression,
62J02,
62M10,
62F12,
60F15
@article{1015952002,
author = {Skouras, K.},
title = {Strong consistency in nonlinear stochastic regression
models},
journal = {Ann. Statist.},
volume = {28},
number = {3},
year = {2000},
pages = { 871-879},
language = {en},
url = {http://dml.mathdoc.fr/item/1015952002}
}
Skouras, K. Strong consistency in nonlinear stochastic regression
models. Ann. Statist., Tome 28 (2000) no. 3, pp. 871-879. http://gdmltest.u-ga.fr/item/1015952002/