Goodness-of-fit tests in parametric regression based on the estimation of the error distribution

Van Keilegom, Ingrid;González Manteiga, Wenceslao;Sánchez Sellero, César
(2004) , 15 pages

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Authors
  • Van Keilegom, IngridUCLouvain
    Author
  • González Manteiga, WenceslaoUniversidad de Santiago de Compostela
    Author
  • Sánchez Sellero, CésarUniversidad de Santiago de Compostela
    Author
Abstract
Consider a heteroscedastic regression model Y = m(X) + σ(X)ε, where m(X) = E(Y|X) and σ2 (X) = Var(Y|X) are unknown and the error ε is independent of the covariate X. We propose a new type of test statistic for testing whether the regression curve m(·) belongs to some parametric family of regression functions. The proposed test statistic measures the distance between the empirical distribution function of the parametric and of the nonparametric residuals. The asymptotic theory of the proposed test is developed and the proposed testing procedure is illustrated by means of a small simulation study and the analysis of a data set.
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Van Keilegom, I., González Manteiga, W., & Sánchez Sellero, C. (2004). Goodness-of-fit tests in parametric regression based on the estimation of the error distribution (STAT Discussion Paper 0405). https://hdl.handle.net/2078.5/33208