Efficiency Improvement for Ordinary Least Square and Orthogonal Regression-An Application in Chemical Engineering
Journal of Engineering Research and Reports · pp. 1–5 · Published 7 Mar 2019
10.9734/jerr/2019/v4i116893Abstract
Regression analysis plays indispensable role in QSAR/QSPR, chemical Engineering, science & technology and research projects. Best fit regression models are constantly a challenge to the researchers, efforts are taken to minimize the error components so that the predictability and efficiency of models increase. Presence of high error component eventually upset the future research and forecasting of the facts. In this paper a technique is introduced that reduces the error component and improves the predictability and efficiency of the model.
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