Hostname: page-component-7b7567c8c-kwt9d Total loading time: 0 Render date: 2026-11-13T23:33:14.505Z Has data issue: false hasContentIssue false
  • English
  • Français

A note on gittins indices for pharmaceutical research

Published online by Cambridge University Press:  01 July 2016

You-Gan Wang and
John Gittins
You-Gan Wang
Affiliation:
University of Oxford
John Gittins*
Affiliation:
University of Oxford
*
∗Postal address for both authors: Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK.
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

The Bernoulli/exponential target process is considered. Such processes have been found useful in modelling the search for active compounds in pharmaceutical research. An inequality is presented which improves a result of Gittins (1989), thus providing a better approximation to the Gittins indices which define the optimal search policy.

Keywords

BANDIT PROCESSDYNAMIC PROGRAMMINGGITTINS INDEXSTOPPING TIMETARGET PROCESSES

Information

Type
Letters to the Editor
Information
Advances in Applied Probability , Volume 23 , Issue 4 , December 1991, pp. 975 - 977
Copyright
Copyright © Applied Probability Trust 1991 

References

Bergman, S. W. and Gittins, J. C. (1985) Statistical Methods for Planning Pharmaceutical Research. Marcel Dekker, New York.Google Scholar
Gittins, J. C. (1989) Multi-armed Bandit Allocation Indices. Wiley, Chichester.Google Scholar
Jones, D. M. (1975) Search Procedures for Industrial Chemical Research. Ph.D. thesis, Cambridge University Engineering Department.Google Scholar
Raiffa, H. and Schlaifer, R. (1961) Applied Statistical Decision Theory. Harvard University Press, Cambridge, MA.Google Scholar