Efficiency Improvement for Ordinary Least Square and Orthogonal Regression-An Application in Chemical Engineering

Khurshid A. Bhat *

State Education Department, Kashmir, Jammu and Kashmir, India.

*Author to whom correspondence should be addressed.


Abstract

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.

Keywords: Regression analysis, internal variable relation, efficiency, orthogonal regression


How to Cite

Bhat, Khurshid A. 2019. “Efficiency Improvement for Ordinary Least Square and Orthogonal Regression-An Application in Chemical Engineering”. Journal of Engineering Research and Reports 4 (1):1-5. https://doi.org/10.9734/jerr/2019/v4i116893.

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