期刊文献+

非线性时间序列建模的均值异方差混合转移分布模型

Expectation heteroscedastic mixture transition distribution model for modeling nonlinear time series
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摘要 进一步研究了由Berchtold提出的均值异方差混合转移分布(expectation heteroscedastic mixture transi- tion distribution model,EHMTD)模型.讨论并得到了EHMTD模型的平稳性条件和分布函数的尾部特征.运用ECM(expectation conditional maximization)算法估计模型的参数.条件分布的多样性使得该类模型能够对非对称、多峰、厚尾等非Gauss特征进行描述.模拟及实例分析的结果表明EHMTD模型是一类易于建模。并且有着广泛应用前景的非线性时间序列模型. The expectation heteroscedastic mixture transition distribution (EHMTD) model first introduced by Berchtold is further studied in this paper. First, the stationary conditions and tail behaviors of the model are derived. The estimation of parameters is easily performed via expectation conditional maximization (ECM) algorithm. The variety of conditional distributions of the EHMTD model makes the model capable of modeling time series with asymmetric multimodal or heavier tail distribution. The model is applied to simulate real data sets with satisfactory results. The EHMTD model is easy to model and potentially useful in modeling nonlinear time series.
出处 《控制理论与应用》 EI CAS CSCD 北大核心 2008年第3期511-516,共6页 Control Theory & Applications
基金 国家自然科学基金(60375003) 教育部重点科研基金(03I53059) 西北工业大学科技创新基金(2007KJ01033).
关键词 平稳性 BIC准则 ECM算法 非对称 多峰 厚尾 条件异方差 stationarity BIC ECM algorithm asymmetric multimodal heavier tail conditonal heteroscedasticity
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参考文献12

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