Bayesian inference about small areas is of considerable current interest, and simultaneous intervals for the parameters for the areas are needed because these parameters are correlated. This is not usually pursued because with many areas the problem becomes difficult. We describe a method for finding simultaneous credible intervals for a relatively large number of parameters, each corresponding...

In this article, we review the concept of a Lévy copula to describe the dependence structure of a bivariate compound Poisson process. In this first statistical approach we consider a parametric model for the Lévy copula and estimate the parameters of the full dependent model based on a maximum likelihood approach. This approach ensures that the estimated model remains in the class of multivaria...

We consider a class of observation-driven Poisson count processes where the current value of the accompanying intensity process depends on previous values of both processes. We show under a contractive condition that the bivariate process has a unique stationary distribution and that the stationary version of the count process is absolutely regular. Moreover, since the intensities can be writte...

The method of maximum likelihood flops when there is linear dependency (multicollinearity) and outlier in the generalized models. In this study, we combined ridge estimator with transformed M-estimator (MT) conditionally unbiased bounded influence (CE). two new estimators are called robust MT Robust-CE. A Monte Carlo study revealed that proposed dominate for models Poisson response log link fun...

Count data with excessive zeros are ubiquitous in healthcare, medical, and scientific studies. There numerous articles that show how to fit Poisson other models which account for the zeros. However, many situations, besides zero, frequency of another count k tends be higher data. The zero- k-inflated distribution model (ZkIP) is appropriate such situations ZkIP essentially a mixture degenerate ...