In recent years, there has been an abundance of research that has used Poisson models and its variants (negative binomial and zero-inflated models) to improve our understanding of the factors that affect accident frequencies on roadway segments. This study explores the application of an alternate method, tobit regression, by viewing vehicle accident rates directly (instead of frequencies) as a ...

Integer-valued time series are often modeled with Markov models or hidden Markov models (HMM). However, when the series represents count data it is often subject to excess zeros. In this case, usual distributions such as binomial or Poisson are unable to estimate the zero mass correctly. In order to overcome this issue, we introduce zero-inflated distributions in the hidden Markov model. The em...

A field study was carried out on the cultivation of yellow diploid potato (Solanum tuberosum Phureja Group) to evaluate influence planting density associated with distances between plants 30, 40, and 50 cm rows paths 100 tuber count sizes less than 2 cm, 2-4 4-6 more 6 cm. At time harvest tubers, they were classified by size respective made. The modelling counts done means usual negative binomi...

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.

Zero-inflated models for count data are becoming quite popular nowadays and are found in many application areas, such as medicine, economics, biology, sociology and so on. However, in practice these counts are often prone to measurement error which in this case boils down to misclassification. Methods to deal with misclassification of counts have been suggested recently, but only for the binomi...

This research develops a mixture regression model that is shown to have advantages over the classical Tobit model in model fit and predictive tests when data are generated from a two step process. Additionally, the model is shown to allow for flexibility in distributional assumptions while nesting the classic Tobit model. A simulated data set is utilized to assess the potential loss in efficien...

In a 1992 Technometrics paper, Lambert (1992, 34, 1-14) described zero-inflated Poisson (ZIP) regression, a class of models for count data with excess zeros. In a ZIP model, a count response variable is assumed to be distributed as a mixture of a Poisson(lambda) distribution and a distribution with point mass of one at zero, with mixing probability p. Both p and lambda are allowed to depend on ...

Commonly used parametric models may lead to erroneous inference when analyzing count or continuous data with excess of zeroes. For non-clustered data, the most commonly used models to address the issue of excess zeroes are zero inflated Poisson (ZIP), zero inflated negative binomial (ZINB), hurdle Poisson (HP) and hurdle negative binomial (HNB). Our goal is to expand these for modeling longitud...