The simulated envelopes of the

negative binomial distribution (Figure 2) showed that the residuals are distributed around the mean and inside the confidence limits; and therefore, the results confirm the good fit of the model.

Nemertean distribution along Mondonguillo beach fits the

negative binomial distribution (Fig.

The

negative binomial distribution was used to build a sequential sampling plan using Wald's (1945) SPRT, on the basis of the number of fruits with at least one mite data.

We fit the transmission data from patients within subgroups to the

negative binomial distribution with mean R and dispersion parameter k, which characterizes individual variation in transmission, including the likelihood of superspreading events (i.e., when infected persons disproportionately transmit the virus to others) (25).

Besides, the P value of

negative binomial distribution is the largest, which means that

negative binomial distribution is able to fit the frequency best.

where NB refers to the

negative binomial distribution with fitted dispersion parameter k and mean [[mu].sub.i] is the expected number of seals in a given block, modeled as the exponential of a linear combination f(.) of the covariates.

The parameters a and b of the beta-binomial model can be chosen to provide flexibility to handle many possible situations in health services research that have this "probability" nature of constraining between 0 and 1, and are more diffuse than the over-dispersion capabilities of the

negative binomial distribution (Morris and Lock 2009).

Exponent k of the

negative binomial distribution: the exponent k is a suitable dispersion index when the size and numbers of sample units are the same in each sample, since this is frequently influenced by the size of the sampling units.

For this reason, the

negative binomial distribution (nbd) was deemed more appropriate than Poisson.

A random variable X has

negative binomial distribution with parameters r>0 and p [member of] (0,1), if [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII], where the binomial coefficient is defined by [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII].

The univariate

negative binomial distribution is uniquely defined in many statistical textbooks.

Thus, when the variance is substantially larger than the mean, overdispersion is suggested and the

negative binomial distribution is considered more appropriate.