Generalized Minimum Perpendicular Distance Square Method of Estimation


In case of heteroscedasticity, a Generalized Minimum Perpendicular Distance Square (GMPDS) method has been suggested instead of traditionally used Generalized Least Square (GLS) method to fit a regression line, with an aim to get a better fitted regression line, so that the estimated line will be closest one to the observed points. Mathematical form of the estimator for the parameters has been presented. A logical argument behind the relationship between the slopes of the lines and has been placed.

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R. Karim, M. Alam, M. Chowdhury and F. Hossain, "Generalized Minimum Perpendicular Distance Square Method of Estimation," Applied Mathematics, Vol. 3 No. 12, 2012, pp. 1945-1949. doi: 10.4236/am.2012.312266.

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The authors declare no conflicts of interest.


[1] W. H. Greene, “Econometric Analysis,” 5th Edition, Pearson Education, Singapore, 2003,
[2] D. Gujarati, “Basic Econometrics,” 4th Edition, McGraw-Hill, New York, 2003.
[3] M. F. Hossain and G. Khalaf, “Minimum Perpendicular Distance Square Method Estimation,” Journal of Applied Statistical Science, Vol. 17, No. 2, 2009, pp. 153-180.
[4] A. Mizrahi and M. Sullivan, “Calculus and Analytic Geometry,” Wadsworth Publishing Company, Beverly, 1986.
[5] M. R. Spiegel and John Lin, “Mathematical Handbook of Formulas and Tables,” 2nd Edition, Mcgraw-Hill, New York, 1999.

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