negative binomial distribution


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negative binomial distribution

[¦neg·əd·iv bī¦nō·mē·əl ‚di·strə′byü·shən]
(statistics)
The distribution of a negative binomial random variable. Also known as Pascal distribution.
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resulting in a negative binomial distribution, which was obtained by mixing the distributions cited in (4) and (5):
Analysis of variance of Bemisia tabaci adult density, sampled in 12 melon fields, to assess the dispersion parameter of the common negative binomial distribution (Kcommon).
Lord, "Estimating dispersion parameter of negative binomial distribution for analysis of crash data: Bootstrapped maximum likelihood method," Transportation Research Record, no.
The use of the negative binomial distribution for the outcome variable ensures that overdispersion (where the variance of the outcome variable is greater than the mean) is also accounted for, something which the Poisson distribution does not do.
The researchers used generalized linear model (GLM) for modelling the frequency of women's visits for ANC, where response followed the negative binomial distribution. For final selection two criterions, including AIC and BIC were used.
We next fit the negative binomial distribution to the transmission data and to various data subsets according to patients' circumstances.
As the negative binomial distribution model has exponential conditional mean, its coefficient estimate can be interpreted as a semi-elasticity (Cameron and Trivedi 2009).
Chance mechanisms generating the negative binomial distribution. In: Random counts in models and structures (ed.
Some other researchers who take this a step further will discuss whether negative binomial distribution or geometric distribution better fits the frequency [6].
In Figure 4, the mean system size of System 2 is shown as a function of [eta] when the service time follows the negative binomial distribution.