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
收藏
页码：593 / 600
页数：8
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