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A bootstrap test for single index models

Single index models are frequently used in econometrics and biometrics. Logit and Probit models arc special cases with fixed link functions. In this paper we consider a bootstrap specification test that detects nonparametric deviations of the link function. The bootstrap is used with the aim to rind...

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Hauptverfasser: Härdle, Wolfgang (VerfasserIn) , Mammen, Enno (VerfasserIn) , Proença, Isabel (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 2001
In: Statistics
Year: 2001, Jahrgang: 35, Heft: 4, Pages: 427-451
ISSN:1029-4910
DOI:10.1080/02331880108802746
Online-Zugang:Verlag, Volltext: http://dx.doi.org/10.1080/02331880108802746
Verlag, Volltext: https://doi.org/10.1080/02331880108802746
Verlag, Volltext: http://www.tandfonline.com/doi/abs/10.1080/02331880108802746
Volltext
Verfasserangaben:Wolfgang Härdle, Enno Mammen, Isabel Proenca

MARC

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520 |a Single index models are frequently used in econometrics and biometrics. Logit and Probit models arc special cases with fixed link functions. In this paper we consider a bootstrap specification test that detects nonparametric deviations of the link function. The bootstrap is used with the aim to rind a more accurate distribution under the null than the normal approximation. We prove that the statistic and its bootstrapped version have the same asymptotic distribution. In a simulation study we show that the bootstrap is able to capture the negative bias and the skewness of the test statistic. It yields better approximations to the true critical values and consequently it has a more accurate level than the normal approximation. 
650 4 |a Bootstrap 
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