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动态模型的最优递归估计AI 解读

This article checks, using both real and simulated data, the effectiveness of modern adaptive techniques to track the parameters of time-varying dynamic models. The real case studies concern a bone marrow transplant data set published by Tong, the gas furnace model of Box and Jenkins, and two series of West German interest rates. Simulation studies focus on ARX models with smoothly and suddenly changing parameters. The general approach is to compare the fitting-forecasting…

动态模型的最优递归估计AI 解读

This article checks, using both real and simulated data, the effectiveness of modern adaptive techniques to track the parameters of time-varying dynamic models. The real case studies concern a bone marrow transplant data set published by Tong, the gas furnace model of Box and Jenkins, and two series of West German interest rates. Simulation studies focus on ARX models with smoothly and suddenly changing parameters. The general approach is to compare the fitting-forecasting…

参数服从 ARIMA 过程的 ARIMA 模型AI 解读

This article introduces a general class of nonlinear and nonstationary time-series models whose basic scheme is an autoregressive integrated moving average (ARIMA). The main feature i s that the parameters are assumed to behave like a vector ARIMAx model in which the exogenous (x) component is represented by the regressors o f the observable process. For this class, a general algorithm of identification-estimation is outlined based on the sampling information alone. The…