background: the aim of this study was to assess the associations between nutrition and dental caries in permanent dentition among schoolchildren. methods: a cross-sectional survey was undertaken on 698 schoolchildren aged 10 to 12 yr from a random sample of primary schools in kermanshah, western iran, in 2014. the study was based on the data obtained from the questionnaire containing informatio...

Abstract We propose a flexible multivariate stochastic model for over-dispersed count data. Our methodology is built upon mixed Poisson random vectors ( Y 1 ,…, d ), where the { i } are conditionally independent variables. The rates of distributions with arbitrary non-negative margins linked by copula function. present basic properties these and provide several examples. A particular case geome...

background : so far, several studies were conducted to estimate the prevalence of cigarette smoking in iran, but none of them used a statistical model to deal with unobserved smokers. the present study planned to estimate the accurate prevalence of cigarette smoking using mixture of truncated poisson distribution. methods : a cross-sectional study was conducted in hamadan, west of iran in 2009,...

The burstiness of Internet traffic was established in pioneering work in the early 1990s, which demonstrated that packet arrival times are not Poisson, and packet and byte counts in fixed-length intervals are long-range dependent [17, 20]. Here we demonstrate that these results are one end of a continuum of traffic characteristics. At the other end are Poisson behavior and independence. Our stu...

Marginal structural models (MSMs) allow estimation of effect modification by baseline covariates, but they are less useful for estimating effect modification by evolving time-varying covariates. Rather, structural nested models (SNMs) were specifically designed to estimate effect modification by time-varying covariates. In their paper, Petersen et al. (Am J Epidemiol 2007;000:000–00) describe h...

Precise identification of the time when a process has changed enables process engineers to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for a Poisson process in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step < /div> change, a linear trend and a known multip...

Time series of event counts are common in political science and other social science applications. Presently, there are few satisfactory methods for identifying the dynamics in such data and accounting for the dynamic processes in event counts regression. We address this issue by building on earlier work for persistent event counts in the Poisson exponentially weighted moving-average model (PEW...

In the present article, we introduce a new true integer valued autoregressive model of order one TPDINAR(1) for data sets on Z and either positive or negative correlations based Poisson difference (Skellam) marginal distribution using random walk variable (It). Properties are derived. We consider several methods estimating unknown parameters model, their properties discussed. Simulations carrie...

The aim of the paper is to provide an exact approach for generating a Poisson process sampled from a hierarchical CRM, without having to instantiate the infinitely many atoms of the random measures. We use completely random measures (CRM) and hierarchical CRM to define a prior for Poisson processes. We derive the marginal distribution of the resultant point process, when the underlying CRM is m...