Semiparametric Maximum Likelihood Estimation of Nonlinear Regression Models and Monte Carlo Evidence.

This paper studies adaptive estimation of nonlinear regression models with i.i.d. error terms . Previously in the literature, the adaptive maximum likelihood (AMLE) has been proposed only when the densities of the error terms are assumed to be symmetric.

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Year of publication:	1997
Authors:	Yang, J.
Institutions:	University of Western Ontario, Department of Economics
Subject:	REGRESSION ANALYSIS \| EVALUATION

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Series:	UWO Department of Economics Working Papers.
Type of publication:	Book / Working Paper
Notes:	56 pages
Classification:	C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data ; C82 - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005515529