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Microcomputer implementation of robust regression techniques

Authors: Detwiler, Dana;

Microcomputer implementation of robust regression techniques

Abstract

Systems Engineering requires that relationships between variables under control (independent variables) and variables which are to be controlled (dependent variables) be quantified. The most common method for characterizing this relationship is to use least squares regression. This method is inadequate in cases where some of the observed relationships between variables is contaminated with aberrant data. This project provides two microcomputer-based tools that will aid the systems engineer in identifying such instances of aberrant observations. Although mainframe implementations of these tools exist, microcomputer implementations of these tools are needed to accommodate many engineers which find microcomputers more accessible than mainframe computers.

Master of Science

Country
United States
Related Organizations
Keywords

LD5655.V851 1993.D478, Regression analysis -- Data processing, Robust statistics -- Data processing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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