A new multivariate zero-inflated binomial distribution has the purpose of analyzing the multivariate proportional data with excessive zeros. The distributional properties of the purposed model are discussed. The Newton Raphson, Fisher score and expectation maximization algorithm are developed for estimating parameters of interest. The score test and the likelihood ratio test are derived for ass...

Count data sometimes exhibit a greater proportion of zero counts than is consistent with the data having been generated by a simple Poisson or negative binomial process. For example, a preponderance of zero counts have been observed in data that record the number of automobile accidents per driver, the number of criminal acts per person, the number of derogatory credit reports per person, the n...

A Bayesian hierarchical model is developed for count data with spatial and temporal correlations as well as excessive zeros, uneven sampling intensities, and inference on missing spots. Our contribution is to develop a model on zero-inflated count data that provides flexibility in modeling spatial patterns in a dynamic manner and also improves the computational efficiency via dimension reductio...

We describe a mixed-effects hurdle model for zero-inflated longitudinal count data, where a baseline variable is included in the model specification. Association between the count data process and the endogenous baseline variable is modeled through a latent structure, assumed to be dependent across equations. We show how model parameters can be estimated in a finite mixture context, allowing fo...

Beta Regression, an extension of generalized linear models, can estimate the effect of explanatory variables on data falling within the (0,1) interval. Recent developments in Beta Regression theory extend the support interval to now include 0 and 1. The %Beta_Regression macro is updated to now allow for Zero-One Inflated Beta Regression.

Single cell RNA-seq data allows insight into normal cellular function and diseases including cancer through the molecular characterisation of cellular state at the single-cell level. Dimensionality reduction of such high-dimensional datasets is essential for visualization and analysis, but single-cell RNA-seq data is challenging for classical dimensionality reduction methods because of the prev...

Excess zeros are encountered in many empirical count data applications. We provide a new explanation of extra zeros, related to the underlying stochastic process that generates events. The process has two rates, a lower rate until the first event, and a higher one thereafter. We derive the corresponding distribution of the number of events during a fixed period and extend it to account for obse...

While both zero-inflation and the unobserved heterogeneity in risks are prevalent issues modeling insurance claim counts, determination of Bayesian credibility premium counts with these features often demanding due to high computational costs associated a use MCMC. This article explores way approximate for claims frequency that follows zero-inflated Poisson distribution via variational Bayes ap...