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Optimization of Regression Models of Experimental Data Using Confirmation PointsA new search metric is discussed that may be used to better assess the predictive capability of different math term combinations during the optimization of a regression model of experimental data. The new search metric can be determined for each tested math term combination if the given experimental data set is split into two subsets. The first subset consists of data points that are only used to determine the coefficients of the regression model. The second subset consists of confirmation points that are exclusively used to test the regression model. The new search metric value is assigned after comparing two values that describe the quality of the fit of each subset. The first value is the standard deviation of the PRESS residuals of the data points. The second value is the standard deviation of the response residuals of the confirmation points. The greater of the two values is used as the new search metric value. This choice guarantees that both standard deviations are always less or equal to the value that is used during the optimization. Experimental data from the calibration of a wind tunnel strain-gage balance is used to illustrate the application of the new search metric. The new search metric ultimately generates an optimized regression model that was already tested at regression model independent confirmation points before it is ever used to predict an unknown response from a set of regressors.
Document ID
20100024271
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Ulbrich, N.
(Jacobs Technology, Inc. Moffett Field, CA, United States)
Date Acquired
August 24, 2013
Publication Date
January 4, 2010
Subject Category
Mathematical And Computer Sciences (General)
Report/Patent Number
ARC-E-DAA-TN1004
AIAA Paper 2010-930
Meeting Information
Meeting: 48th AIAA Aerospace Sciences Meeting
Location: Orlando, FL
Country: United States
Start Date: January 4, 2010
End Date: January 7, 2010
Sponsors: American Inst. of Aeronautics and Astronautics
Funding Number(s)
CONTRACT_GRANT: NNA09DB39C
Distribution Limits
Public
Copyright
Public Use Permitted.
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