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The best estimate and 95% confidence intervals from two separate feeds were calculated using a negative binomial model as previously described54 without zero inflation.
Using a negative binomial regression, we found that several factors jointly influence the retweeting of software vulnerability messages.
Thus Chambers et al. (2014) consider M-estimation for overdispersed counts using a negative binomial model.
We then fitted each of the 46,130 distance distributions using a negative binomial distribution function, and generated the corresponding cumulative density functions giving the p value as a function of the city block distance (Fig. 1i).
All five hypotheses presented in this research were tested by using a negative binomial regression analysis to determine what variables influenced the number of visits a country received by IUU fishing vessels.
Inference was corroborated using a negative binomial model fitted in Stata v10.
Counts of T. tenuis worms were fitted to models using a negative binomial error distribution (Genmod procedure; SAS, 2001).
An alternative linear regression on non-transformed data, using a negative binomial error structure, did not lead to better results.
Since this is not the case in Illumina data, we model an overdispersed Poisson distribution by using a negative binomial distribution.
AL data were counts and were therefore fitted to models using a negative binomial error distribution and a log link function in PROC GLIMMIX.
Instead, we analysed the IEF using a negative binomial regression.
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