FAST LIKELIHOOD EVALUATION AND PREDICTION FOR NONSTATIONARY STATE-SPACE MODELS

被引：0

作者：

DEJONG, P ^{[1
]}

CHUCHUNLIN, S ^{[1
]}

机构：

[1] NATL UNIV SINGAPORE,FAC BUSINESS ADM,DEPT DECIS SCI,SINGAPORE 0511,SINGAPORE

来源：

BIOMETRIKA | 1994年 / 81卷 / 01期

关键词：

ARIMA MODEL; BASIC STRUCTURAL MODEL; DIFFUSE; KALMAN FILTER; LIKELIHOOD; NONSTATIONARITY; PREDICTION; STATE SPACE;

D O I：

暂无

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

A recursive procedure for initializing the Kalman filter is displayed. The recursion is for nonstationary state space models. The procedure imposes small computational and programming burden over and above the Kalman filter. The procedure is superior to other suggested approaches in both computational speed and general applicability. General properties of the method are investigated. Details of the initialization for the ARIMA (p, d, q) and basic structural models are considered.

引用

页码：133 / 142

页数：10

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