Nonlinear maximum likelihood estimation of autoregressive time series

被引：6

作者：

McWhorter, LT

Scharf, LL

机构：

[1] Department of Electrical and Computer Engineering, University of Colorado, Boulder

来源：

IEEE TRANSACTIONS ON SIGNAL PROCESSING | 1995年 / 43卷 / 12期

关键词：

D O I：

10.1109/78.476434

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we describe an algorithm for finding the exact, nonlinear, maximum likelihood (ML) estimators for the parameters of an autoregressive time series. We demonstrate that the ML normal equations can be written as an interdependent set of cubic and quadratic equations in the AR polynomial coefficients. We present an algorithm that algebraically solves this set of nonlinear equations for low-order problems. For high-order problems, we describe iterative algorithms for obtaining a ML solution.

引用

页码：2909 / 2919

页数：11

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