To Develop Accurate Model for Prediction of Soil Attributes with The Help of Statistical Modelling Techniques Such as Multiple Linear Regression (MLR) And Partial Least Square Regression (PLSR)

P. M. Shah¹ , D. C. Vyas²

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.2 , pp.99-102, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijsrmss/v6i2.99102

Online published on Apr 30, 2019

Copyright © P. M. Shah, D. C. Vyas . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Present research paper signifies the importance of two statistical modelling techniques, Multiple Linear Regression (MLR) and partial Least Square Regression (PLSR). In the present study above mentioned methods are used to develop accurate model for prediction of soil property. MLR showes better result in comparison to PLSR in terms of Regression coefficient. In future, present models can be extended for soil data set of various other regions.

Key-Words / Index Term :
soil pH, multiple linear regression, partial least square regression (PLSR)

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