Identification of Nonlinear Time Series from First Order Cumulative Characteristics
Identification of Nonlinear Time Series from First Order Cumulative Characteristics
复制标题
从一阶累积特性辨识非线性时间序列
DOI：
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发表时间：
1994
期刊：
影响因子：
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通讯作者：
Mei‐jie Zhang
中科院分区：
文献类型：
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作者：
I. McKeague;Mei‐jie Zhang
翻译后摘要：我们考虑的问题，识别类的时间序列模型的一系列属于观察的一部分系列的基础上。非参数估计技术已被应用到这个问题的各个作者使用核估计的一步滞后条件均值和方差函数。我们研究累积版本的Tukey回归图估计这样的功能。这些比均值和方差函数本身的估计值更稳定，可用于构建置信带。还开发了特定参数模型的拟合优度检验。
Abstract : We consider the problem of identifying the class of time series model to which a series belongs based on observation of part of the series. Techniques of nonparametric estimation have been applied to this problem by various authors using kernel estimates of the one-step lagged conditional mean and variance functions. We study cumulative versions of Tukey regressogram estimators of such functions. These are more stable than estimates of the mean and variance functions themselves and can be used to construct confidence bands. Goodness of fit tests for specific parametric models are also developed.