| 1. | The probability of any particular result is the multinomial distribution,
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| 2. | Various methods may be used to simulate a multinomial distribution.
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| 3. | However, conflating the categorical and multinomial distributions can lead to problems.
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| 4. | In that case, you may want to look at multinomial distribution.
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| 5. | This equals ( refer to multinomial distribution for details)
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| 6. | For the multinomial distribution the analog to the Bernoulli Distribution is the categorical distribution.
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| 7. | Relative species abundances in the UNTB model follow a zero-sum multinomial distribution.
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| 8. | In general, distributions that result from a finite or infinite Dirichlet-multinomial distributions.
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| 9. | It is this positive correlation which gives rise to overdispersion relative to the multinomial distribution.
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| 10. | In the two cases, the result is a multinomial distribution with " k " categories.
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