A new Markov Chain Monte Carlo algorithm that allows parallel processing has been described in a previous paper (“Markov Chain Monte Carlo Calculations Allowing Parallel Processing Using a Variant of the Metropolis Algorithm”) that appeared in this journal in 2010. In this second follow-on paper, the problem of calculating the normalization integral of the distribution function is considered. I...

In this paper the first passage problem is examined for linear and nonlinear systems driven by Poissonian and normal white noise input. The problem is handled step-by-step accounting for the Markov properties of the response process and then by Chapman–Kolmogorov equation. The final formulation consists just of a sequence of matrix–vector multiplications giving the reliability density function ...

A new approach for modeling under reported Poisson counts is developed The parameters of the model are estimated by Markov Chain Monte Carlo simulation An application to workers absenteeism data from the German Socio Economic Panel illustrates the fruitfulness of the approach Worker absenteeism and the level of pay are unrelated but absence rates increase with rm size I had helpful discussions ...

Will reading habit influence your life? Many say yes. Reading markov chains gibbs fields monte carlo simulation and queues is a good habit; you can develop this habit to be such interesting way. Yeah, reading habit will not only make you have any favourite activity. It will be one of guidance of your life. When reading has become a habit, you will not make it as disturbing activities or as bori...

This paper is concerned with the problem of determining the e*ect of a binary treatment variable on a continuous outcome given longitudinal observational data and non-randomly assigned treatments. A general semiparametric Bayesian model (based on Dirichlet process mixing) is developed which contains potential outcomes and subject level outcome-speci0c random e*ects. The model is subjected to a ...