Support Points of Locally Optimal Designs for Nonlinear Models with Two Parameters

MOspace/Manakin Repository

Breadcrumbs Navigation

Support Points of Locally Optimal Designs for Nonlinear Models with Two Parameters

Please use this identifier to cite or link to this item: http://hdl.handle.net/10355/9127

[+] show full item record


Title: Support Points of Locally Optimal Designs for Nonlinear Models with Two Parameters
Author: Yang, Min, 1970 Oct. 28-; Stufken, John
Keywords: binary response
generalized linear model
Loewner order
Date: 2009
Publisher: Institute of Mathematical Statistics
Citation: The Annals of Statistics 2009, Vol. 37, No. 1, 518-541.
Abstract: 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.
URI: http://hdl.handle.net/10355/9127

This item appears in the following Collection(s)

  • Statistics publications (MU) [18]
    The items in this collection are the scholarly output of the faculty, staff, and students of the Department of Statistics.

[+] show full item record