*Correspondence: [email protected] 1Department of Mathematics, Ohio University, Athens, OH, USA Full list of author information is available at the end of the article Abstract Poisson-Tweedie mixtures are the Poisson mixtures for which the mixing measure is generated by those members of the family of Tweedie distributions whose support is non-negative. This class of non-negative integer-valued ...

The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features of these methods, a new implementation of hurdle and zero-inflated regression models in the functions ...

BACKGROUND Within longitudinal epidemiological research, 'count' outcome variables with an excess of zeros frequently occur. Although these outcomes are frequently analysed with a linear mixed model, or a Poisson mixed model, a two-part mixed model would be better in analysing outcome variables with an excess of zeros. Therefore, objective of this paper was to introduce the relatively 'new' met...

Various statistical methods have been used to measure the impact of treatment on chronic obstructive pulmonary disease (COPD) exacerbations. Poisson regression has recently been recommended as the appropriate method but the model does not satisfactorily account for variability between patients. In contrast, use of a negative binomial model, which corresponds to assuming a separate Poisson param...

Applications of zero-inflated count data models have proliferated in health economics. However, zero-inflated Poisson or zero-inflated negative binomial maximum likelihood estimators are not robust to misspecification. This article proposes Poisson quasi-likelihood estimators as an alternative. These estimators are consistent in the presence of excess zeros without having to specify the full di...

SUMMARY There has been much recent interest in Bayesian inference for generalized additive and related models. The increasing popularity of Bayesian methods for these and other model classes is mainly caused by the introduction of Markov chain Monte Carlo (MCMC) simulation techniques which allow the estimation of very complex and realistic models. This paper describes the capabilities of the pu...

The Lee-Carter (LC) model led to the development of many prominent mortality models. This study aims modify generalised linear (GLM) (Poisson, negative binomial, and binomial) framework LC by incorporating factors that affect into model. top three which for each 14 countries studied were selected using random forest recursive feature elimination (RF-RFE) method eliminates least important based ...

Aim: This study was conducted to model the relationship between discrete dependent variable (yellow stem borer population) and continuous weather variables.
 Data Description: The yellow (YSB) population standard meteorological week (SMW) wise variables (temperature, relative humidity, rainfall sunshine hours) data of Warangal centre (Telangana state) generated under All India Co-Ordinated...