Experimental Design to Maximize Information

@inproceedings{SebastianiExperimentalDT,
  title={Experimental Design to Maximize Information},
  author={Paola Sebastiani and Henry P. Wynn}
}
This paper will consider different methods to measure the gain of information that an experiment provides on parameters of a statistical model. The approach we follow is Bayesian and relies on the assumption that information about model parameters is represented by their probability distribution so that a measure of information is any summary of the probability distributions satisfying some sensible assumptions. Robustness issues will be considered and investigated in some examples using a new… CONTINUE READING

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References

Publications referenced by this paper.
Showing 1-10 of 25 references

and H

  • P. Sebastian
  • P. Wynn, “Renyi-type entropies and distances in…
  • 2000
Highly Influential
5 Excerpts

On a measure of information provided by an experiment,” Annals of Mathematical Statistics, 27, pp

  • D. V. Lindley
  • 986–1005,
  • 1956
Highly Influential
3 Excerpts

Maximum entropy sampling and optimal Bayesian experimental design,” Journal of the Royal Statistical Society, B, 62, pp

  • P. Sebastiani, H. P. Wynn
  • 145–157,
  • 2000
1 Excerpt

Coherent dispersion criteria for optimal experimental design

  • A. P. Dawid, P. Sebastiani
  • Annals of Statistics
  • 1999

Coherent dispersion criteria for optimal experimental design,” Annals of Statistics, 27, pp

  • A. P. Dawid, P. Sebastiani
  • 65–81,
  • 1999
1 Excerpt

and A

  • L. Pronzato, H. P. Wynn
  • A. Zhigljavsky, Dynamical Search, Chapman and…
  • 1999
1 Excerpt

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