Modeling Cassava Yield: A Response Surface Approach
Adeshina Oyedele Bello
TL;DR
This paper applies experimental design and nonlinear bootstrap regression in R to model cassava yield, demonstrating the invariant property of parameter estimates in the inverse polynomial model.
Contribution
It introduces a novel combination of graphical experimental design techniques and bootstrap regression for modeling crop yield.
Findings
Parameter estimates are invariant in the inverse polynomial model.
Graphical techniques aid in experimental design.
Bootstrap regression enhances model robustness.
Abstract
This paper reports on application of theory of experimental design using graphical techniques in R programming language and application of nonlinear bootstrap regression method to demonstrate the invariant property of parameter estimates of the Inverse polynomial Model (IPM) in a nonlinear surface.
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Taxonomy
TopicsOptimal Experimental Design Methods