Detecting the Shift in the Probability of Success in a Series of Bernoulli Trails,
Abstract
The determination of a stopping rule for the detection of the time of an increase in the success probability of a sequence of independent Bernoulli trials is discussed. Both success probabilities are assumed unknown. A Bayesian approach is applied; the distribution of the location of the shift in the success probability is assumed geometric and the success probabilities are assumed to have a known joint prior distribution. The costs involved are penalties for late or early stoppings. The nature of the optimal dynamic programming solution is discussed and a procedure for obtaining a suboptimal stopping rule is determined. The results indicate that the detection procedure is quite effective. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 23, 1977
- Accession Number
- ADA042739
Entities
People
- S. Zacks
- Z. Barzily
Organizations
- George Washington University