Sentence examples for models for counts from inspiring English sources
As described in the Additional file 1 (Benecha et al. 2017), the marginalized models proposed in this article belong to a larger class of marginalized mixture models for counts.
With the aim of expanding the pool of two-part marginalized models for counts, special consideration is given to data generating mechanisms based on mixtures of two Poissons and a negative binomial with a Poisson distribution.
An extensive literature describes models for counts [ 2- 8], and they have been commonly applied in economic analyses, traffic accidents, and health services utilization.
Linear mixed models for continuous outcomes and generalized linear mixed models for counts and categorical outcomes will be used to assess treatment effects with respect to primary and secondary outcome measures.
Additional file 1 Marginalized Mixture Models for Count Data from Multiple Source Populations.
As the observed information on property crimes is given in count form (see Section 4 for details), non-linear regression models for count data should be used.
Regression models for count and binary data that control for underreporting were developed and used, as underreporting is a major concern in crime self-reports.
In the last few years, research on the time series models for count data has become a popular topic in the literature.
The models for count variables had a better performance when predicting diseased animals and also had a similar performance between them.
Software defect prediction comprises two major procedures: (i) Design of appropriate software metrics to represent characteristic software system properties; and (ii) development of effective regression models for count data, allowing for accurate prediction of the number of software defects.
We examined the variation in species richness and abundance of landbirds by season (fixed effect) and habitat type (nested within seasons) for Lakeba using generalized linear mixed effects Poisson models (for count data).
