ASYMPTOTIC INFERENCE FOR DYNAMICAL-SYSTEMS OBSERVED WITH ERROR

被引：4

作者：

MACEACHERN, SN ^{[1
]}

BERLINER, LM ^{[1
]}

机构：

[1] OHIO STATE UNIV,DEPT STAT,COLUMBUS,OH 43210

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 1995年 / 46卷 / 03期

基金：

美国国家科学基金会;

关键词：

ASYMPTOTICS; CHAOS; DYNAMICAL SYSTEMS; EXPONENTIAL FAMILIES; LIKELIHOOD RATIO TESTS;

D O I：

10.1016/0378-3758(94)00117-E

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 this article, the effects of measuring a dynamical system with error are investigated. In particular, we assume that the measurement errors follow a distribution in the exponential family, and that the value of the underlying dynamical system determines the parameter of the measurement distribution. The key questions are whether two distinct initial conditions can be asymptotically distinguished and whether two distinct parameter values can be asymptotically distinguished. Results of the statistical theory are applied in the context of dynamical systems.

引用

页码：277 / 292

页数：16

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