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On Bayesian estimation of multinomial probabilities under incomplete experimental information

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URI: https://hdl.handle.net/10016/1317
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ws080503.pdf (301.45 KB)
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2008-02
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In this work, we discuss Bayesian estimation of multinomial probabilities associated with a finite alphabet A under incomplete experimental information. Two types of prior information are considered: (i) number of letters needed to see a particular pattern for the first time, and (ii) the fact that for two fixed words one appeared before the other.
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Patterns, Stopping times, Incomplete experimental information
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DES - Working Papers. Statistics and Econometrics. WS