On the use of Nonparametric Regression in Assessing Parametic Regression Model

Title: On the use of Nonparametric Regression in Assessing Parametic Regression Model
Creator: Brown, Scott; Heathcote, A.
Relation: Journal of Mathematical Psychology Vol. 46, Issue 6, p. 716-730
Publisher Link: http://dx.doi.org/10.1006/jmps.2002.1421
Publisher: Elsevier Science B.V.
Resource Type: journal article
Date: 2002
Description: We develop a new method for assessing the adequacy of a smooth regression function, based on nonparametric regression and the bootstrap. Our methodology allows users to detect systematic misfit and to test hypotheses of the form “the proposed smooth regression model is not significantly different from the smooth regression model that generated these data”. We also provide confidence bands on the location of nonparametric regression estimates assuming that the proposed regression function is true, allowing users to pinpoint regions of misfit. We illustrate the application of the new method, using local linear nonparametric regression, both where an error model is assumed, and where the error model is an unknown nonstationary function of the predictor.
Subject: smooth regression function; nonparametric regression estimates
Identifier: uon:2021
Identifier: http://hdl.handle.net/1959.13/27939
Identifier: ISSN:0022-2496
Language: eng
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