HIERARCHICAL POLYNOMIAL REGRESSION MODELS - CONSTRUCTIONS AND COMPARISONS

PRAMIT PANDIT¹*, V. MANJUNATH², K.N. KRISHNAMURTHY^3
1Department of Agricultural Statistics, Applied Mathematics and Computer Science, University of Agricultural Sciences, Bengaluru, Karnataka, 560 065, India
²Department of Agricultural Statistics, Applied Mathematics and Computer Science, University of Agricultural Sciences, Bengaluru, Karnataka, 560 065, India
³Department of Agricultural Statistics, Applied Mathematics and Computer Science, University of Agricultural Sciences, Bengaluru, Karnataka, 560 065, India
* Corresponding Author : pramitpandit@gmail.com

Received : 15-09-2018     Accepted : 26-09-2018     Published : 30-09-2018
Volume : 10     Issue : 18       Pages : 7145 - 7146
Int J Agr Sci 10.18 (2018):7145-7146

Keywords : Construction of models, Hierarchical polynomial regression models, Forward selection method, Backward elimination method, Regression Models
Conflict of Interest : None declared
Acknowledgements/Funding : Author thankful to Department of Agricultural Statistics, Applied Mathematics and Computer Science, University of Agricultural Sciences, Bengaluru, Karnataka, 560 065, India
Author Contribution : All author equally contributed

A model is called to be a hierarchical polynomial regression model if all the lower order terms are present along with the highest order term(s). These models plays very significant role for the purpose of reparameterizations, Simplification in writing computer programs for polynomial model development and restricting our focus on few well-formulated models instead of all possible regression models. By the methods of stepwise regressions, backward elimination and forward selection, hierarchical polynomial regression models have been constructed.

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