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PROBABILITY‐BASED OPTIMAL DESIGN
Author(s) -
McGree J. M.,
Eccleston J. A.
Publication year - 2008
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/j.1467-842x.2007.00497.x
Subject(s) - outcome (game theory) , mathematics , class (philosophy) , mathematical optimization , optimal design , range (aeronautics) , statistics , computer science , artificial intelligence , mathematical economics , engineering , aerospace engineering
Summary Optimal design of experiments has generally concentrated on parameter estimation and, to a much lesser degree, on model discrimination. Often an experimenter is interested in a particular outcome and wishes to maximize in some way the probability of this outcome. We propose a new class of compound criteria and designs that address this issue for generalized linear models. The criteria offer a method of achieving designs that possess the properties of efficient parameter estimation and a high probability of a desired outcome.