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A delimitation of the support of optimal designs for Kiefer’s [formula omitted]-class of criteria

Authors
Journal
Statistics & Probability Letters
0167-7152
Publisher
Elsevier
Volume
83
Issue
12
Identifiers
DOI: 10.1016/j.spl.2013.09.009
Keywords
  • Approximate Design
  • Optimum Design
  • Support Points
  • Design Algorithm
Disciplines
  • Computer Science
  • Design

Abstract

Abstract The paper extends the result of Harman and Pronzato [Harman, R., Pronzato, L., 2007. Improvements on removing non-optimal support points in D-optimum design algorithms. Statistics & Probability Letters 77, 90–94], which corresponds to p=0, to all strictly concave criteria in Kiefer’s ϕp-class. We show that, for any given design measure ξ, any support point x∗ of a ϕp-optimal design is such that the directional derivative of ϕp at ξ in the direction of the delta measure at x∗ is larger than some bound hp[ξ] which is easily computed.

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