Integrated Statistical and Engineering Process Control Based on Smooth Transition Autoregressive Model

Traditional studies on integrated statistical process control and engineering process control (SPC-EPC) are based on linear autoregressive integrated moving average (ARIMA) time series models to describe the dynamic noise of the system.However,linear models sometimes are unable to model complex nonlinear autocorrelation.To solve this problem,this paper presents an integrated SPC-EPC method based on smooth transition autoregressive (STAR) time series model,and builds a minimum mean squared error (MMSE) controller as well as an integrated SPC-EPC control system.The performance of this method for checking the trend and sustained shift is analyzed.The simulation results indicate that this integrated SPC-EPC control method based on STAR model is effective in controlling complex nonlinear systems.

基于STAR模型的人民币实际汇率行为的描述

本文应用平滑过渡自回归(STAR)模型来揭示人民币实际汇率的动态行为。研究发现,以logistic函数作为过渡函数的STAR模型能很好地描述人民币实际汇率的行为。模型表明,在存在两种不同的制度下,人民币实际汇率表现出不同的动态特征,且在两个不同制度之间的转换是迅速的。

人民币实际汇率的非线性特征研究

本文通过采用不同的线性和非线性一元时间序列模型对人民币实际汇率行为进行研究。研究结果表明,非线性的自我激励阈值自回归模型和平滑过渡自回归模型对人民币实际汇率历史数据有很好的拟合效果,且人民币实际汇率具有显著的非线性动态行为特征。