SUPPORT POINTS OF LOCALLY OPTIMAL DESIGNS FOR NONLINEAR MODELS WITH TWO PARAMETERS
By Min Yang, John Stufken. 2009
86 citations recorded by the source corpus.
We propose a new approach for identifying the support points of a locally optimal design when the model is a nonlinear model. In contrast to the commonly used geometric approach, we use an approach based on algebraic tools. Considerations are restricted to models with two parameters, and the general results are applied to often used special cases, including logistic, probit, double exponential and double reciprocal models for binary data, a loglinear Poisson regression model for count data, and the Michaelis-Menten model. The approach, which is also of value for multi-stage experiments, works both with constrained and unconstrained design regions and is relatively easy to implement.
Subfields: Computational Theory and Mathematics, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/f0632e916ef73c6fd0b5b9ee3762a6aa5f155c0a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Holger Dette
- Viatcheslav B. Melas
- Min Yang
- Bin Zhang
- Shuguang Huang
- Luc Pronzato
- Andrej Pázman
- John Stufken
In Management Science and Operations Research
- Min Yang
- Stefanie Biedermann
- Elina Tang
- Holger Dette
- Viatcheslav B. Melas
- Bin Zhang
- Shuguang Huang
- John Stufken
In Statistics and Probability
- Min Yang
- Stefanie Biedermann
- Elina Tang
- Holger Dette
- Viatcheslav B. Melas
- I. Van Keilegom
- Natalie Neumeyer
- Johan Segers
Citations in the corpus
- OPTIMAL DESIGNS FOR GENERALIZED LINEAR MODELS WITH MULTIPLE DESIGN VARIABLES (2011, background): “of Yang and Stufken (2009). The conclusion follows an application of that proposition.”
- On Optimal Designs for Nonlinear Models: A General and Efficient Algorithm (2013, background): “Recently, Yang and Stufken (2009), Yang (2010), and Dette and Melas (2011) obtained a series of unifying results for a large class of nonlinear models, multiple optimality criteria, and multiple objectives.”
- A note on the de la Garza phenomenon for locally optimal designs (2011, background): “These results generalize recent findings of Yang and Stufken (2009) for nonlinear models with two parameters.”