Nonparametric bootstrap tests for neglected nonlinearity in time series regression models
Nonparametric bootstrap tests for neglected nonlinearity in time series regression models
复制标题
时间序列回归模型中被忽略的非线性的非参数自举测试
DOI：
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发表时间：
2001
期刊：
影响因子：
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通讯作者：
A. Ullah
中科院分区：
文献类型：
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作者：
Tae;A. Ullah
给出了各种非参数核回归估计，在此基础上，我们考虑了时间序列回归模型中忽略非线性的两种非参数检验。其中一个是蔡、范和姚（2000）的拟合优度检验，另一个是李和王（1998）和郑（1996）的非参数条件矩检验。Bootstrap程序用于这些测试，并通过蒙特卡洛实验，特别是条件异方差误差检查其性能。
Various nonparametric kernel regression estimators are presented, based on which we consider two nonparametric tests for neglected nonlinearity in time series regression models. One of them is the goodness-of-fit test of Cai, Fan and Yao (2000) and another is the nonparametric conditional moment test by Li and Wang (1998) and Zheng (1996). Bootstrap procedures are used for these tests and their performance is examined via monte carlo experiments, especially with conditionally heteroskedastic errors.