background : to prepare safe and adequate blood supply to meet patients’ needs and ensure a sufficient number of regular blood donors, knowledge about factors encouraging people to donate blood regularly is essential. considering its importance, we aimed to identifying the effective factors of the return to blood donation in based on zero-inflated count regression models using bayesian approach...

Abstract This article considers bivariate mixed Poisson INAR(1) regression models with correlated random effects for modelling correlations of different signs and magnitude among time series types claim counts. is the first that proposed family used in a statistical or actuarial context. For expository purposes, count Lognormal Gamma paired via Gaussian copula are presented as competitive alter...

AIM The aim of this study was to compare alternatives methods for analysis of zero inflated count data and compare them with simple count models that are used by researchers frequently for such zero inflated data. BACKGROUND Analysis of viral load and risk factors could predict likelihood of achieving sustain virological response (SVR). This information is useful to protect a person from acqu...

The study investigated the robustness of Quantile regression count data over negative binomial regression, when there is overdispersion and presence outlier. made use a complete with 30% missing which was imputed using Multiple Imputation by Chain Equation (MICE) in R also an outlier injected into during imputation values. Regression Negative Binomial estimates were compared their model fits co...

This research aims to analyze the comparison of Poisson and Binomial Negative modeling causative factors gum abscess incidence in West Java. The methods used are Regression Negative. Predictors this habit eating sweet foods (X1), consumption sugary drinks (X2), never going a dental medical personnel (X3). results study obtained AIC values negative binomial models smaller than regression model. ...