Bivariate non‐parametric regression models: simulations and applications

Alessandra Durio and Ennio Davide Isaia

Applied Stochastic Models in Business and Industry, 2004, vol. 20, issue 3, 291-303

Abstract: This paper presents a practical procedure for performing non‐parametric bivariate regression analysis. The procedure applies the Nadaraya–Watson local linear kernel estimator with associated bootstrap variability bands whenever the pseudo‐likelihood ratio test rejects the linear regression model hypothesis. Two case studies and simulations are used to demonstrate the proposed technique. Calculations have been performed using the shareware R software. Copyright © 2004 John Wiley & Sons, Ltd.

Date: 2004
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https://doi.org/10.1002/asmb.527

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Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:20:y:2004:i:3:p:291-303

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