Skip to main content
SpringerLink
Log in

A consistent estimator for nonlinear regression models

  • Published:
Metrika Aims and scope Submit manuscript

Abstract

In this paper an estimator for the general (nonlinear) regression model with random regressors is studied which is based on the Fourier transform of a certain weight function. Consistency and asymptotic normality of the estimator are established and simulation results are presented to illustrate the theoretical ones.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Author information

Authors and Affiliations

  1. Faculty of Informatics, University of Debrecen, P. O. Box 12, H-4010, Debrecen, Hungary

    S. Baran

Authors
  1. S. Baran
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. Baran.

Additional information

Supported by the Hungarian National Science Foundation OTKA under Grants No. F 032060/2000 and F 046061/2004 and by the Bolyai Grant of the Hungarian Academy of Sciences.

Received October 2003

Rights and permissions

Reprints and permissions

About this article

Cite this article

Baran, S. A consistent estimator for nonlinear regression models. Metrika 62, 1–15 (2005). https://doi.org/10.1007/s001840400349

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s001840400349

Keywords

Search

Navigation