AN EFFICIENT COMPUTATIONAL TECHNIQUE FOR GENERALIZED APPLICATION OF MAXIMUM-LIKELIHOOD TO IMPROVE CORRELATION OF EXPERIMENTAL-DATA

被引：17

作者：

FARISS, RH

LAW, VH

机构：

[1] Monsanto P and R Company, Indian Orchard, MA 01151

[2] Department of Computer Science, Tulane University, New Orleans

来源：

COMPUTERS & CHEMICAL ENGINEERING | 1979年 / 3卷 / 1-4期

关键词：

D O I：

10.1016/0098-1354(79)80020-4

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A practical systematic approach is presented for extending application of the maximum likelihood criterion to obtain optimum correlations of experimental data without requiring the usual very restrictive assumptions: Gaussian response error dispersion, plus pre-known error or specially structured error relationships. Two examples are described: one illustrates non-linear correlation with unknown measurement errors in both dependent and independent variables; in the other, distortion of correlation due to ahigh incidence of 'outlier' response values is virtually eliminated by use of a generalized non-Gaussian error dispersion form. © 1979.

引用

页码：95 / 104

页数：10

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