ESTIMATING MODEL VARIANCE IN THE CASE OF UNDERMODELING

被引：19

作者：

HJALMARSSON, H ^{[1
]}

LJUNG, L ^{[1
]}

机构：

[1] LINKOPING UNIV,DEPT ELECT ENGN,S-58183 LINKOPING,SWEDEN

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 1992年 / 37卷 / 07期

关键词：

D O I：

10.1109/9.148358

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A reliable quality estimate of a given model is a prerequisite for any reasonable use of the model. The model error consists of two different contributions: the bias error and the random error. In this contribution, we show how the size (variance) of the random error can be reliably estimated in the case where a true system description cannot be achieved in the model structure used. This consistent error estimate can differ considerably from the conventionally used variance estimates which thus, could be quite misleading.

引用

页码：1004 / 1008

页数：5