Bias in nonlinear regression model with heteroscedastic or Ar(1) error structure

We investigate the biases of the maximum likelihood estimators from normal nonlinear regression models. Emphasis is placed on the heteroscedastic and first order autoregressive error structure. Bias reduction after the parameter transformation is also discussed.

MoreLess

Year of publication:	1989
Authors:	Tsai, Chih-Ling
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 8.1989, 2, p. 167-170
Publisher:	Elsevier
Subject:	autocorrelation bias heteroscedasticity transformation

More details

Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005319485