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Performance studies of the measurement test for detection of gross errors in process data
Author(s) -
Iordache C.,
Mah R. S. H.,
Tamhane A. C.
Publication year - 1985
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.690310717
Subject(s) - observational error , process (computing) , error detection and correction , test (biology) , position (finance) , computer science , standard deviation , test data , standard error , reliability engineering , statistics , mathematics , algorithm , engineering , paleontology , finance , economics , biology , programming language , operating system
The measurement test proposed by Mah and Tamhane (1982) allows the gross error associated with a measurement to be directly identified without a separate procedure. In this paper a comprehensive evaluation of this test was carried out based on two different definitions of its power. The influence of constraints, network configuration, position of measurement, magnitudes of gross error and standard deviations, number of measurements, and other factors were summarized as rules and guidelines for the application of this test. The simulation procedure developed in this investigation may be used to design a gross error detection scheme for any specific application.