Microbiome omics data including 16S rRNA reveal intriguing dynamic associations between
the human microbiome and various disease states. Drastic changes in microbiota can be …

Zero inflated distributions are used in a wide variety of phenomena, particularly when the
response variable exhibits an excessive number of zeros. These phenomena can lead to an …

The Poisson distribution is often used as a standard model for count data. Quite often,
however, such data sets are not well fit by a Poisson model because they have more zeros …

Count data are widely existed in the fields of medical trials, public health, surveys and
environmental studies. In analyzing count data, it is important to find out whether the zero …

Zero-inflated and hurdle models are widely applied to count data possessing excess zeros,
where they can simultaneously model the process from how the zeros were generated and …

Objectives The aim of this study was to show the potential of B ayesian analysis in statistical
modelling of dental caries data. Because of the bounded nature of the dmft (DMFT) index …

Estimates of county-level disease prevalence have a variety of applications. Such estimation
is often done via model-based small-area estimation using survey data. However, for …

In many sampling involving non negative integer data models, the number of zeros is
observed to be significantly higher than the expected number in the assumed model. Such …

In many practical applications, count data often exhibit greater or less variability than
allowed by the equality of mean and variance, referred to as overdispersion/underdispersion …

Relational count data are often obtained from sources such as simultaneous purchase in
online shops and social networking service information. Clustering such relational count …