Optimal estimating equations for state vectors in non-Gaussian and nonlinear state space time series models

被引：0

作者：

Durbin, J ^{[1
]}

机构：

[1] Univ London London Sch Econ & Polit Sci, London, England

来源：

SELECTED PROCEEDINGS OF THE SYMPOSIUM ON ESTIMATING FUNCTIONS | 1997年 / 32卷

关键词：

nonlinear time series; non-Gaussian time series; posterior mode estimates; estimating functions;

D O I：

10.1214/lnms/1215455051

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In state space times series models the development over time of the observed series is determined by an unobserved series of state vectors. The paper considers the estimation of these vectors by the mode of the posterior distribution of the state vectors given the data. It is shown that the estimates are the solution of an optimal unbiased estimating equation.

引用

页码：285 / 291

页数：7

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