POLYNOMIAL SPLINE CONFIDENCE BANDS FOR REGRESSION CURVES

被引:1
|
作者
Wang, Jing [1 ]
Yang, Lijian [2 ]
机构
[1] Univ Illinois, Dept Math Stat & Comp Sci, Chicago, IL 60607 USA
[2] Michigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USA
基金
美国国家科学基金会;
关键词
Brownian bridge; B spline; knots; nonparametric regression; quantile transformation; LOCAL ASYMPTOTICS; MAXIMAL DEVIATION; TENSOR-PRODUCTS;
D O I
暂无
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Asymptotically exact and conservative confidence bands are obtained for a nonparametric regression function, using piecewise constant and piecewise linear spline estimation, respectively. Compared to the pointwise confidence interval of Huang (2003), the confidence bands are inflated by a factor proportional to {log (n)}(1/2), with the same width order as the Nadaraya-Watson bands of Hardle (1989), and the local polynomial bands of Xia (1998) and Claeskens and Van Keilegom (2003). Simulation experiments corroborate the asymptotic theory. The linear spline band has been used to identify an appropriate polynomial trend for fossil data.
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页码:325 / 342
页数:18
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