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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| Main Authors: | , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
2001
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| In: |
Statistics
Year: 2001, Volume: 35, Issue: 4, Pages: 427-451 |
| ISSN: | 1029-4910 |
| DOI: | 10.1080/02331880108802746 |
| Online Access: | Volltext Volltext Volltext 
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| Author Notes: | Wolfgang Härdle, Enno Mammen, Isabel Proenca |
| Summary: | 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. |
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| Item Description: | Published online: 27 Jun 2007 Gesehen am 12.02.2018 |
| Physical Description: | Online Resource |
| ISSN: | 1029-4910 |
| DOI: | 10.1080/02331880108802746 |