D-optimal designs for Poisson regression with synergetic interaction effect

Abstract

We characterize D-optimal designs in the two-dimensional Poisson regression model with synergetic interaction and provide an explicit proof. The proof is based on the idea of reparameterization of the design region in terms of contours of constant intensity. This approach leads to a substantial reduction in complexity as properties of the sensitivity can be treated along and across the contours separately. Furthermore, some extensions of this result to higher dimensions are presented.

Optimal Planting Density and Nutrient Application of Soybeans: A Case Study in Northeastern China

“…In this study, we conducted an experimental design to optimize soybean yield. Given the high requirement for the goodness of fit of the regression equation and the challenge of dealing with a large number of experimental treatments, we employed the D-optimization regression approach as delineated in prior works [44][45][46]. This method not only ensures precise parameter estimation but also reduces the requisite number of experimental data points, thus resulting in a cost-effective approach from an experimental perspective.…”