This paper presents a Bayesian approach to the regression analysis of truncated data, with a focus on zero-truncated counts from the Poisson distribution. The approach provides inference not only on the regression coefficients but also on the total sample size and the parameters of the covariate distribution. The theory is applied to some illegal immigrant data from The Netherlands. Several mod...

aspirin is one of the certified medicines commonly used for the secondary prevention of myocardial infarction (mi). aspirin side effects and gastrointestinal bleeding, in particular, have arisen debates on its use for the primary prevention of mi. the present research evaluates the cost-effectiveness of the use of aspirin in the primary prevention of mi among iranian men with average cardiovasc...

b a c k g r o u n d & aim: the aim of the current study was to investigate the advantages of bayesian method in comparison to traditional methods to detect best antioxidant in freezing of human male gametes. methods  &  materials:   semen  samples  were  obtained  from  40  men  whose  sperm  had  normal criteria. a part of each sample was separated without antioxidant  as fresh and the remaini...

we propose to use a mathematical method based on stochastic comparisons of markov chains in order to derive performance indice bounds‎. ‎the main goal of this paper is to investigate various monotonicity properties of a single server retrial queue with first-come-first-served (fcfs) orbit and general retrial times using the stochastic ordering techniques‎.

We derive two models of viral epidemiology on connected networks and compare results to simulations. The differential equation model easily predicts the expected long term behavior by defining a boundary between survival and extinction regions. The discrete Markov model captures the short term behavior dependent on initial conditions, providing extinction probabilities and the fluctuations arou...

Variable selection techniques for the classical linear regression model have been widely investigated. Variable selection in fully nonparametric and additive regression models has been studied more recently. A Bayesian approach for nonparametric additive regression models is considered, where the functions in the additivemodel are expanded in a B-spline basis and a multivariate Laplace prior is...

Many efforts have been involved in association study of quantitative phenotypes and expressed genes. The key issue is how to efficiently identify phenotype-associated genes using appropriate methods. The limitations for the existing approaches are discussed. We propose a hierarchical mixture model in which the relationship between gene expressions and phenotypic values is described using orthog...

We develop an algorithm to construct approximate decision rules that are piecewise-linear and continuous for DSGE models with occasionally-binding constraint. The functional form of the allows us derive a conditionally optimal particle filter (COPF) evaluation likelihood function exploits structure solution. document accuracy approximation embed it into Markov chain Monte Carlo conduct Bayesian...

landsat data for 1992, 2000, and 2013 land use changes for ekbatan dam watershed was simulated through ca-markov” model. two classification methods were initially used, viz. the maximum likelihood (mal) and support vector machine (svm). although both methods showed high overall accuracy and kappa coefficient, visually mal failed in separating land uses, particularly built up and dry lands.there...