This paper presents a control charting technique to monitor attribute data based on a generalized zero-inflated Poisson (GZIP) distribution, which is an extension of ZIP distribution. GZIP distribution is very flexible in modeling complicated behaviors of the data. Both the technique of fitting the GZIP model and the technique of designing control charts to monitor the attribute data based on t...

There has been a considerable amount of work devoted by transportation safety analysts to the development and application of new and innovative models for analyzing crash data. One important characteristic about crash data that has been documented in the literature is related to datasets that contained a large amount of zeros and a long or heavy tail (which creates highly dispersed data). For s...

We consider the problem of locating multiple interacting quantitative trait loci (QTL) influencing traits measured in counts. In many applications the distribution of the count variable has a spike at zero. Zero-inflated generalized Poisson regression (ZIGPR) allows for an additional probability mass at zero and hence an improvement in the detection of significant loci. Classical model selectio...

Background: The number of failed courses and semesters in students are indicatorsof their performance. These amounts have zero inflated (ZI) distributions. Using ZI Poisson and negative binomial distributions we can model these count data to find the associated factors and estimate the parameters. This study aims at to investigate the important factors related to the educational performance of ...

Several kinds of models have been developed in modeling the occurrence of crashes, but most of these models have deficiencies and lack good results. Single and multivariate deterministic models have illustrated some influences of causal factors on crashes, but the inherent deterministic characteristic of these models makes explaining crash events a difficult task for these kinds of models. Stoc...

The Poisson regression is a popular approach in modeling count data. However, many situations often the variance of data greater than mean (over-dispersed data) and generalized or mixed models such as gamma (negative binomial), inverse Gaussian, lognormal, Lindley have been proposed alternatives to for describing over-dispersed In some situations, source over-dispersion large percentage zeros d...

Medical and public health research often involve the analysis of count data that exhibit a substantially large proportion of zeros, such as the number of heart attacks and the number of days of missed primary activities in a given period. A zero-inflated Poisson regression model, which hypothesizes a two-point heterogeneity in the population characterized by a binary random effect, is generally...