Testing for no effect in nonparametric regression via spline smoothing techniques /
We propose three statistics for testing that a predictor variable has no effect on the response variable in regression analysis. The test statistics are integrals of squared derivatives of various orders of a periodic smoothing spline fit to the data. The large sample properties of the test statisti...
| Main Author: | |
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| Format: | Book |
| Language: | English |
| Published: |
College Station, Texas :
Department of Statistics, Texas A & M University,
1992.
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| Series: | Technical report (Texas A & M University. Department of Statistics) ;
no. 174. |
| Subjects: |
| Summary: | We propose three statistics for testing that a predictor variable has no effect on the response variable in regression analysis. The test statistics are integrals of squared derivatives of various orders of a periodic smoothing spline fit to the data. The large sample properties of the test statistics are investigated under the null hypothesis and sequences of local alternatives and a Monte Carlo study is conducted to assess finite sample power properties. |
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| Physical Description: | 20 leaves ; 28 cm |
| Bibliography: | Includes bibliographical references (leaves 18-20). |