On the evaluation of the information matrix for multiplicative seasonal time-series models

被引:7
|
作者
Godolphin, EJ [1 ]
Bane, SR [1 ]
机构
[1] Royal Holloway Univ London, London, England
关键词
asymptotic covariance matrix; autoregressive moving average time series; Fisher information matrix; maximum likelihood estimation; multiplicative seasonal model;
D O I
10.1111/j.1467-9892.2005.00461.x
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper gives a procedure for evaluating the Fisher information matrix for a general multiplicative seasonal autoregressive moving average time-series model. The method is based on the well-known integral specification of Whittle [Ark. Mat. Fys. Astr. (1953) vol. 2. pp. 423-434] and leads to a system of linear equations, which is independent of the seasonal period and has a closed solution. It is shown to be much simpler, in general, than the method of Klein and Melard [Journal of Time Series Analysis (1990) vol. 11, pp. 231-237], which depends on the seasonal period. It is also shown that the nonseasonal method of McLeod [Biometrika (1984) vol. 71, pp. 207-211] has the same basic features as that of Klein and Melard. Explicit solutions are obtained for the simpler nonseasonal and seasonal models in common use, a feature which has not been attempted with the Klein-Melard or the McLeod approaches. Several illustrations of these results are discussed in detail.
引用
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页码:167 / 190
页数:24
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