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Sample size planning for testing significance of curves

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  • Hsiao-Hsian Gao
  • Li-Shan Huang

Abstract

Smoothing methods for curve estimation have received considerable attention in statistics with a wide range of applications. However, to our knowledge, sample size planning for testing significance of curves has not been discussed in the literature. This paper focuses on sample size calculations for nonparametric regression and partially linear models based on local linear estimators. We describe explicit procedures for sample size calculations based on non- and semi-parametric F-tests. Data examples are provided to demonstrate the use of the procedures.

Suggested Citation

  • Hsiao-Hsian Gao & Li-Shan Huang, 2016. "Sample size planning for testing significance of curves," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(11), pages 2019-2028, August.
    • Handle: RePEc:taf:japsta:v:43:y:2016:i:11:p:2019-2028
    DOI: 10.1080/02664763.2015.1126238
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    1. Jianqing Fan & Wenyang Zhang, 2000. "Simultaneous Confidence Bands and Hypothesis Testing in Varying‐coefficient Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(4), pages 715-731, December.
    2. Huang, Li-Shan & Davidson, Philip W., 2010. "Analysis of Variance and F-Tests for Partial Linear Models With Applications to Environmental Health Data," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 991-1004.
    3. Li, Qi, 2000. "Efficient Estimation of Additive Partially Linear Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 41(4), pages 1073-1092, November.
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