A two-sample test for the error distribution in nonparametric regression based on the characteristic function
| Autor: | J. L. Moreno-Rebollo, María Dolores Jiménez-Gamero, G. I. Rivas-Martínez |
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| Rok vydání: | 2017 |
| Předmět: |
Statistics and Probability
Anderson–Darling test 010103 numerical & computational mathematics Kolmogorov–Smirnov test 01 natural sciences 010104 statistics & probability symbols.namesake Sampling distribution F-test Statistics Test statistic symbols Null distribution Z-test F-test of equality of variances 0101 mathematics Statistics Probability and Uncertainty Mathematics |
| Zdroj: | Statistical Papers. 60:1369-1395 |
| ISSN: | 1613-9798 0932-5026 |
| Popis: | A test for the equality of error distributions in two nonparametric regression models is proposed. The test statistic is based on comparing the empirical characteristic functions of the residuals calculated from independent samples of the models. The asymptotic null distribution of the test statistic cannot be used to estimate its null distribution because it is unknown, since it depends on the unknown common error distribution. To approximate the null distribution, a weighted bootstrap estimator is studied, providing a consistent estimator. The finite sample performance of this approximation as well as the power of the resulting test are evaluated by means of a simulation study. The procedure can be extended to testing for the equality of $$d>2$$ error distributions. |
| Databáze: | OpenAIRE |
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