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Asymptotics for polynomial spline regression under weak conditions

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  • Huang, Jianhua Z.

Abstract

We derive rate of convergence for spline regression under weak conditions. The results improve upon those in Huang (Ann. Statist. 26 (1998a) 242) in two ways. Firstly, results are obtained under less stringent conditions on the growing rate of the number of knots. Secondly, L2 approximation instead of L[infinity] approximation by splines are used to bound the rate of convergence, this allows us to obtain results when the regression function or its components in ANOVA decomposition are in broader function classes.

Suggested Citation

  • Huang, Jianhua Z., 2003. "Asymptotics for polynomial spline regression under weak conditions," Statistics & Probability Letters, Elsevier, vol. 65(3), pages 207-216, November.
  • Handle: RePEc:eee:stapro:v:65:y:2003:i:3:p:207-216
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    References listed on IDEAS

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    1. Huang, Jianhua Z., 1998. "Functional ANOVA Models for Generalized Regression," Journal of Multivariate Analysis, Elsevier, vol. 67(1), pages 49-71, October.
    2. He, Xuming & Shi, Peide, 1996. "Bivariate Tensor-Product B-Splines in a Partly Linear Model," Journal of Multivariate Analysis, Elsevier, vol. 58(2), pages 162-181, August.
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    Cited by:

    1. Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Kato, Kengo, 2015. "Some new asymptotic theory for least squares series: Pointwise and uniform results," Journal of Econometrics, Elsevier, vol. 186(2), pages 345-366.
    2. Yu, Lili & Peace, Karl E., 2012. "Spline nonparametric quasi-likelihood regression within the frame of the accelerated failure time model," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2675-2687.
    3. Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2012. "Gaussian approximation of suprema of empirical processes," CeMMAP working papers CWP44/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Holland, Ashley D., 2017. "Penalized spline estimation in the partially linear model," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 211-235.
    5. Chen, Xiaohong & Christensen, Timothy M., 2015. "Optimal uniform convergence rates and asymptotic normality for series estimators under weak dependence and weak conditions," Journal of Econometrics, Elsevier, vol. 188(2), pages 447-465.
    6. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2013. "On the asymptotic theory for least squares series: pointwise and uniform results," CeMMAP working papers CWP73/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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