@article{ajams2019734,
author={{B.O., Onyegbuchulem and M.T, Nwakuya and J.C, Nwabueze and Otu, Otu Archibong},
title={Choice of Appropriate Power Transformation of Skewed Distribution for Quantile Regression Model},
journal={American Journal of Applied Mathematics and Statistics},
volume={7},
number={3},
pages={105--111},
year={2019},
url={http://pubs.sciepub.com/ajams/7/3/4},
issn={2328-7292},
abstract={Quantile Regression (QR) performed better than Ordinary Least Square (OLS) when the Data is skewed. Its best result can be achieved when the Data is transformed. Quantreg package of R software was used to illustrate the various power transformation fitness for quantile regression model. The analysis shows that the best result was obtained from the square root of y transformation with an average error term <img src=image/abs1.png></img> of 0.9539, -0.0494, 0.0238, -0.5309 and -0.7544 for 10th, 25th, 50th, 75th and 90<SUP>th</SUP> quantile respectively. From the results obtained, it shows that model transformation can greatly improve the result of quantile regression model.},
doi={10.12691/ajams-7-3-4}
publisher={Science and Education Publishing}
}