A simple consistent bootstrap test for a parametric regression function
A simple consistent bootstrap test for a parametric regression function
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DOI：
10.1016/s0304-4076(98)00011-6
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发表时间：
1998-11-01
影响因子：
6.3
通讯作者：
Wang, SJ
中科院分区：
文献类型：
--
作者：
Li, Q;Wang, SJ
考虑了参数回归函数型的简单一致性检验，提出了检验参数回归函数型的Bootstrap方法。结果表明，自举法比渐近正态理论结果更精确地逼近检验的零分布。我们还提出了一个一致的测试测试参数部分线性模型与半参数部分线性替代。蒙特卡罗模拟表明，基于“野生自举”临界值，自举检验表现良好。(C)1998年Elsevier Science S.A. All rights reserved.
A simple consistent test is considered and a bootstrap method is proposed for testing a parametric regression functional form. It is shown that the bootstrap method gives a more accurate approximation to the null distribution of the test than the asymptotic normal theory result. We also propose a consistent test for testing a parametric partially linear model versus a semiparametric partially linear alternative. Monte Carlo simulations suggest that the bootstrap test performs well based on 'wild bootstrap' critical values. (C) 1998 Elsevier Science S.A. All rights reserved.