Suppose that there are finitely many simple hypotheses about the unknown arrival rate and mark distribution of a compound Poisson process, and that exactly one of them is correct. The objective is to determine the correct hypothesis with minimal error probability and as soon as possible after the observation of the process starts. This problem is formulated in a Bayesian framework, and its solution is presented. Provably convergent numerical methods and practical near-optimal strategies are described and illustrated on various examples.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Modeling and Simulation
- Compound Poisson processes
- Optimal stopping
- Sequential analysis
- Sequential hypothesis testing