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On the sequential construction of optimum bounded designs

Authors
  • Pronzato, Luc
Publication Date
Jan 01, 2006
Identifiers
DOI: 10.1016/j.jspi.2004.10.020
OAI: oai:HAL:hal-00416063v1
Source
HAL
Keywords
Language
English
License
Unknown
External links

Abstract

We consider a parameter estimation problem with independent observations where one samples from a finite population of independent and identically distributed experimental conditions X. The size of the population is N but only n samples, a proportion alpha of N, can be used. The quality of a sample is measured by a regular optimality criterion phi(.) based on the information matrix, such as the D-criterion. The construction of an optimal approximate design bounded by mu/alpha, with mu the probability measure of X, can be used to construct a sampling strategy which is asymptotically optimum (when the size N of the population tends to infinity). We show that a sequential strategy which does not require any information on mu is also asymptotically optimum. Some possible applications are indicated.

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