Maximum likelihood estimation of Gaussian models with missing data-Eight equivalent formulations

被引：11

作者：

Hansson, Anders ^{[1
]}

Wallin, Ragnar ^{[1
]}

机构：

[1] Linkoping Univ, Div Automat Control, SE-58183 Linkoping, Sweden

来源：

AUTOMATICA | 2012年 / 48卷 / 09期

关键词：

Maximum likelihood estimation; Missing data; Expectation-maximization algorithm; ARMAX models; EM ALGORITHM; TIME-SERIES;

D O I：

10.1016/j.automatica.2012.05.060

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper we derive the maximum likelihood problem for missing data from a Gaussian model. We present in total eight different equivalent formulations of the resulting optimization problem, four out of which are nonlinear least squares formulations. Among these formulations are also formulations based on the expectation-maximization algorithm. Expressions for the derivatives needed in order to solve the optimization problems are presented. We also present numerical comparisons for two of the formulations for an ARMAX model. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：1955 / 1962

页数：8

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