Minimax Sequential Testing for Poisson Processes
Fuente:
arXiv
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866908335018606592 |
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| author | Mei, Hongwei |
| author_facet | Mei, Hongwei |
| contents | Suppose we observe a Poisson process in real time for which the intensity may take on two possible values $λ_0$ and $λ_1$. Suppose further that the priori probability of the true intensity is not given. We solve a minimax version of Bayesian problem of sequential testing of two simple hypotheses to minimize a linear combination of the probability of wrong detection and the expected waiting time in the worst scenario of all possible priori distributions. An equivalent characterization for the least favorable distributions is derived and a sufficient condition for the existence is concluded. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_04084 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Minimax Sequential Testing for Poisson Processes Mei, Hongwei Statistics Theory Optimization and Control Suppose we observe a Poisson process in real time for which the intensity may take on two possible values $λ_0$ and $λ_1$. Suppose further that the priori probability of the true intensity is not given. We solve a minimax version of Bayesian problem of sequential testing of two simple hypotheses to minimize a linear combination of the probability of wrong detection and the expected waiting time in the worst scenario of all possible priori distributions. An equivalent characterization for the least favorable distributions is derived and a sufficient condition for the existence is concluded. |
| title | Minimax Sequential Testing for Poisson Processes |
| topic | Statistics Theory Optimization and Control |
| url | https://arxiv.org/abs/2311.04084 |