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Adaptive designs for optimal observed Fisher information

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  • Adam Lane

Abstract

Expected Fisher information can be found a priori and as a result its inverse is the primary variance approximation used in the design of experiments. This is in contrast with the common claim that the inverse of the observed Fisher information is a better approximation of the variance of the maximum likelihood estimator. Observed Fisher information cannot be known a priori; however, if an experiment is conducted sequentially, in a series of runs, the observed Fisher information from previous runs is known. In the current work, two adaptive designs are proposed that use the observed Fisher information from previous runs to inform the design of future runs.

Suggested Citation

  • Adam Lane, 2020. "Adaptive designs for optimal observed Fisher information," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(4), pages 1029-1058, September.
    • Handle: RePEc:bla:jorssb:v:82:y:2020:i:4:p:1029-1058
    DOI: 10.1111/rssb.12378
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    References listed on IDEAS

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    1. Mizera, Ivan & Müller, Christine H., 2002. "Breakdown points of Cauchy regression-scale estimators," Statistics & Probability Letters, Elsevier, vol. 57(1), pages 79-89, March.
    2. Rolf Sundberg, 2003. "Conditional statistical inference and quantification of relevance," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 299-315, February.
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