一类双重时间序列模型的预报  

THE FORECASTING OF SOME DOVBLY TIME SERIES MODELS

作　　者：张宏性 

机构地区：[1]国家统计局统计研究所,北京100826

出　　处：《应用概率统计》1992年第3期256-261,共6页Chinese Journal of Applied Probability and Statistics

摘　　要：满足 x_t-A_0=(θ_t+α)x_t-1+α_t的时间序列模型称为双重时序模型.其中{α_t}是正态平稳白噪声序列,{θ_t}为一个随机序列.本文给出了当{θt}服从 AR(1)或 MA(1)模型时,{x_t}的多步最小方差预报及其与适时线性最小方差预报的计算机模拟对比。A doubly time series model is defined to satisfy the relation X_t-A_0=(θ_t+a)X_(t-1)+ α_1 where{θ_g:t=0,1,2,…}is itself a stochastic series,and{α_t:t=0,1,2…}is white noise with Eα_t^2=σ~2.When{θ_g:t=0,1,2,…}satisfy AR(1)or MA(1)model,this paper gives out poly-steps minimum mean square error forecast of{X_t,t=0,1,2…}, and the comparison of its properties with updated linear minimum mean square error forecasted by computer simulation.

关 键 词：双重时序模型 预报 随机序列 

分 类 号：O211.5[理学—概率论与数理统计]