Bayesian inference for multinomial probabilities from a stopping time sample information

M. R. Sillero Denamiel, P. Ramirez Cobo, B. Vidakovic

We undertake Bayesian inference of multinomial probabilities associated with a finite alphabet, under incomplete experimental information. Specifically, we observe the stopping time variable representing the number of letters needed to see a particular pattern for the first time. The procedure is extended to the case where for two fixed words, one appeared before the other. An application of the method to a reliability problem will be shown.

Keywords: Patterns, stopping times, incomplete experimental information, exact Bayesian inference

Scheduled

GT11.BAYES3 Invited Session
November 9, 2023 4:50 PM
HC4: Sacristía Room

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Bayesian inference for multinomial probabilities from a stopping time sample information

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