The problem of detection of a change in distribution is considered. Shiryayev (1963, Theory Probab. Appl., 8, pp. 22-46, 247-264 and 402-413; 1978, Optimal Stopping Rules, Springer, New York) solved the problem in a Bayesian framework assuming that the prior on the change point is Geometric (p). Shiryayev showed that the Bayes solution prescribes stopping as soon as the posterior probability of the change having occurred exceeds a fixed level. In this paper, a myopic policy is studied. An empirical Bayes stopping time is investigated for detecting a change in distribution when the prior is not completely known.
|Original language||English (US)|
|Number of pages||18|
|Journal||Annals of the Institute of Statistical Mathematics|
|Publication status||Published - Jan 1 1996|
- Bayes sequential rules
- Change points
- Empirical Bayes
- Statistical process control
- Stopping times
ASJC Scopus subject areas
- Statistics and Probability
Empirical bayes detection of a change in distribution. / Karunamuni, Rohana J.; Zhang, Shunpu.In: Annals of the Institute of Statistical Mathematics, Vol. 48, No. 2, 01.01.1996, p. 229-246.
Research output: Contribution to journal › Article