Consistent specification test for partially linear models with the k-nearest-neighbor method. (English) Zbl 1416.62256
Summary: This study proposes a consistent test for the partially linear model based on the k-nearest-neighbor estimation method. The test statistic has an asymptotic normal distribution under the null hypothesis and diverges to positive infinity when the null hypothesis is false. Simulations show that the estimated power of the proposed test is better than that of the kernel method when the data have heavy tails.
MSC:
| 62G10 | Nonparametric hypothesis testing |
| 62J05 | Linear regression; mixed models |
| 62G20 | Asymptotic properties of nonparametric inference |
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