This paper focuses on the Least Square (LS) regression using the mean and Quantile (M) regression analysis using median which is based on “well-Known” parametric estimation methodologies. Data from Oregon and California highway bridges were used for the comparison of the two methods. Relationships were developed to predict the unit cost of FRP repair work and FRP cost was found to have a high degree of correlation with FRP area for both Oregon and California. It was observed that the Cost Estimating Relationships (CERs) obtained by Quantile (M) regression method had the smaller Mean Absolute Deviation (MAD) values and lower Mean Absolute Percentage Error (MAPE) values than Least Square (LS) regression. The stuudy showed that Quantile Regression is much less sensitive to outliers than Least Squares Regression.
3f. (2014, november 04). 3f-fr. Retrieved November 13, 2014, From 3f-fr: http://3ffr. com/?lang=en.
Barrodale, I. and Roberts, F. D. K., "Solution of an overdetermined system of equations in the L1 norm." Communications of the Association for Computing Machinery, 17, pp 319 320. 1974
Buhai, S. "Quantile regression: Overview and selected applications," Ad-Astra-The Young
Romanian Scientists' Journal, 4, 2004
Foussier, P. "Improving CER Building:Basing A CER On The Median". Journal Of Cost Analysis And Parametrics, 1-3.24, 2010
Hald, A. "A History Of Parametric Statistical Inference From Bernoulli To Fisher,1713-
1935," Choice Reviews Online , 44-6209-44- 6209.25., 2007
Koenker, R. . Quantile Regression. Cambridge: Cambridge University Press, 1- 30, 2005
Koenker, R. W., & d'Orey, V. "Algorithm AS 229: Computing regression quantiles," Applied Statistics, 383-393, 1987
ORDINARY LEAST SQUARES REGRESSION (Social Science). (n.d.). Retrieved June 30, 2014, From http://whatwhen-how.com/social-sciences/ordinaryleast-squares-regression-social-science/.
Ordinary Least Squares Regression. (2008). In W. A. Darity, Jr. (Ed.), International Encyclopedia of the Social Sciences (2nd ed., Vol. 6, pp. 57-61). Detroit: Macmillan Reference USA.
Xia, S. The Multicollinearity Problem-A Comparison Of Ordinary Least Squares And Some Alternative Regression Methods. Ann Arbor: Copyright Proquest, UMI Dissertations Publishing 2009.
Yıl 2016,
Cilt: 6 Sayı: 4, 1293 - 1305, 28.12.2016
3f. (2014, november 04). 3f-fr. Retrieved November 13, 2014, From 3f-fr: http://3ffr. com/?lang=en.
Barrodale, I. and Roberts, F. D. K., "Solution of an overdetermined system of equations in the L1 norm." Communications of the Association for Computing Machinery, 17, pp 319 320. 1974
Buhai, S. "Quantile regression: Overview and selected applications," Ad-Astra-The Young
Romanian Scientists' Journal, 4, 2004
Foussier, P. "Improving CER Building:Basing A CER On The Median". Journal Of Cost Analysis And Parametrics, 1-3.24, 2010
Hald, A. "A History Of Parametric Statistical Inference From Bernoulli To Fisher,1713-
1935," Choice Reviews Online , 44-6209-44- 6209.25., 2007
Koenker, R. . Quantile Regression. Cambridge: Cambridge University Press, 1- 30, 2005
Koenker, R. W., & d'Orey, V. "Algorithm AS 229: Computing regression quantiles," Applied Statistics, 383-393, 1987
ORDINARY LEAST SQUARES REGRESSION (Social Science). (n.d.). Retrieved June 30, 2014, From http://whatwhen-how.com/social-sciences/ordinaryleast-squares-regression-social-science/.
Ordinary Least Squares Regression. (2008). In W. A. Darity, Jr. (Ed.), International Encyclopedia of the Social Sciences (2nd ed., Vol. 6, pp. 57-61). Detroit: Macmillan Reference USA.
Xia, S. The Multicollinearity Problem-A Comparison Of Ordinary Least Squares And Some Alternative Regression Methods. Ann Arbor: Copyright Proquest, UMI Dissertations Publishing 2009.
Pamulaparthy, A. R., Creese, R. C., Gangarao, H. V., Jarıdı, M. (2016). Cost Estimation Comparisons Between Least Square Regression and Quantile Regression on Fiber Reinforced Bridge Projects. International Journal of Electronics Mechanical and Mechatronics Engineering, 6(4), 1293-1305.