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Activity Number: 41
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
Sponsor: Business and Economic Statistics Section
Abstract #318587
Title: An Approach of Fitting Regression Line Not Based on Least Square Estimates
Author(s): Silvey Shamsi* and Mian Adnan and Rahmatullah Imon
Companies: Ball State University and Ball State University and Ball State University
Keywords: Absolute Deviation ; Coefficient of Fit ; Intercept ; Outlier ; Retransformation

All the existing regression estimates suffer from scale problem that exaggerate the contribution of extreme observation(s) as well as outlier(s). Unlike the traditional fitting procedures of regression line based on the least squares estimates; it uses one dimensional transformed deviation for minimizing the total sum of errors. Interestingly enough it is notified that, the estimators have been made a link to the ratio estimators. These estimators also suggest a new approach of quantifying the quality of estimation in the presence of abridged errors, detecting outlier, etc in regression analysis.

Authors who are presenting talks have a * after their name.

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