Interior Analysis for the Minimum Sum of Absolute Errors Regression


Narula, Subhash C.; Wellington, John F.   (1985, ASQC and the American Statistical Association)   Virginia Commonwealth University, Richmond, VA; Gannon University, Erie, PA

Technometrics    Vol. 27    No. 2
QICID: 9205    May 1985    pp. 181-188
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Article Abstract

In this article we study the effect of each observation in a data set on the minimum sum of absolute errors (MSAE) regression. First, we study the extent to which the value of a response variable for an observation can be changed without affecting the MSAE regression fit and then show that MSAE regression is less sensitive to certain types of discrepant observations. Second, we study the effect of deleting an observation on parameter estimation. We illustrate the analysis with examples.


Case study,Diagnostics,Statistical methods,Values,Linear models,Sensitivity analysis

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