A note on the de la Garza phenomenon for locally optimal designs

By Holger Dette, Viatcheslav B. Melas. 2011

57 citations recorded by the source corpus.

The celebrated de la Garza phenomenon states that for a polynomial regression model of degree p — 1 any optimal design can be based on at most p design points. In a remarkable paper, Yang [Ann. Statist. 38 (2010) 2499― 2524] showed that this phenomenon exists in many locally optimal design problems for nonlinear models. In the present note, we present a different view point on these findings using results about moment theory and Chebyshev systems. In particular, we show that this phenomenon occurs in an even larger class of models than considered so far.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/eb56327dfd2122bc6a3d50ceab8ab914a9c0b899

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. Min Yang
2. Stefanie Biedermann
3. John Stufken
4. Elina Tang

In Statistics and Probability

1. Min Yang
2. Stefanie Biedermann
3. John Stufken
4. Elina Tang

Citations in the corpus

• IDENTIFYING LOCALLY OPTIMAL DESIGNS FOR NONLINEAR MODELS: A SIMPLE EXTENSION WITH PROFOUND CONSEQUENCES (2012, methodology): “The work presented here is an extension of Yang and Stufken (2009), Yang (2010) and Dette and Melas (2011). The analytic approach in those papers unified and extended many of the results on locally optimal designs that were available through the so-called geometric approach.”
• On Optimal Designs for Nonlinear Models: A General and Efficient Algorithm (2013, methodology): “Dette, Melas, and Shpilev (2011) studied optimal designs for estimating the derivative of the expected response in nonlinear regression models.”