Asymptotic theory of least squares estimator in a nonregular nonlinear regression model

The asymptotic properties of the least squares estimator are derived for a nonregular nonlinear model via the study of weak convergence of the least squares process. This approach was adapted earlier by the author in the smooth case. The model discussed here is not amenable to analysis via the normal equations and Taylor expansions used by earlier authors.

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Year of publication:	1985
Authors:	Rao, B. L. S. Prakasa
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 3.1985, 1, p. 15-18
Publisher:	Elsevier
Keywords:	weak convergence least squares process regression model

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

Persistent link: https://www.econbiz.de/10005254118