Robust estimation of measurement error variance/covariance from process sampling data

被引：24

作者：

Chen, J ^{[1
]}

Bandoni, A ^{[1
]}

Romagnoli, JA ^{[1
]}

机构：

[1] UNIV SYDNEY,DEPT CHEM ENGN,ICI PROC ENGN LAB,SYDNEY,NSW 2006,AUSTRALIA

来源：

COMPUTERS & CHEMICAL ENGINEERING | 1997年 / 21卷 / 06期

关键词：

D O I：

10.1016/S0098-1354(96)00295-5

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Classical approaches to variance/covariance estimations are very sensitive to outliers. In the present paper a robust approach, based on an M-estimator, is proposed. Monte Carlo simulations show that the strategy provides better results than conventional indirect methods under the presence of outliers. Two examples of application are provided; dealing with both uncorrelated and correlated errors. (C) 1997 Elsevier Science Ltd.

引用

页码：593 / 600

页数：8

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