异方差回归—时序模型  

HETEROSCEDASTIC MODEL OF REGRESSION-TIME SERIES

作　　者：马小兵[1] 傅惠民[1] 

机构地区：[1]北京航空航天大学小样本技术研究中心,北京100083

出　　处：《机械强度》2006年第1期51-54,共4页Journal of Mechanical Strength

基　　金：国防科技预研项目(413200204)资助~~

摘　　要：提出一种异方差回归—时序模型,通过建立回归分析残差的标准差自回归方程,给出回归系数、自回归系数和滑动平均系数的最小二乘估计和极大似然估计。该模型能够在小样本情况下充分发挥回归分析和时间序列各自的优点,对回归模型的残差项进行有效补偿,提高回归分析的精度。文中对回归模型残差相互独立和自相关两种情况分别进行讨论。大量计算表明,该方法具有较高的分析和预测精度。A heteroseedastic model of regression-time series is established. Based on the autoregression equation for the standard variation of the residual errors obtained by ordinary regression analysis, the least square estimates and the maximum likelihood estimates for the regression, the autoregressiun and the moving average coefficients are derived. The model ean exploit the particular advantages of regression analysis and time series under the condition of the small sample, and make compensation for the residual errors of regression model to increase its precision. Both the independent and the correlated residual errors are respectively discussed in detail, Calculations show that higher precision can he gained by using the present method than the traditional one in analysis and prediction.

关 键 词：回归分析 时间序列 异方差 回归一时序模型 小样本 

分 类 号：O211[理学—概率论与数理统计] TB114[理学—数学]