normal 0 false false false en-us x-none fa microsoftinternetexplorer4 aim : for the purpose of cost modeling, the semi-parametric single-index two-part model was utilized in the paper. furthermore, as functional gastrointestinal diseases which are well-known as common causes of illness among the society people in terms of both the number of patients and prevalence in a specific time interval, t...

We provide a comprehensive semi-parametric study of Bayesian partially identified econometric models. While the existing literature on Bayesian partial identification has mostly focused on the structural parameter, our primary focus is on Bayesian credible sets (BCS’s) of the unknown identified set and the posterior distribution of its support function. We construct a (two-sided) BCS based on t...

We test an explanatory model of Internet firm duration after their initial public offerings (IPOs) using a Cox proportional hazards model and a semi-parametric Bayesian survival analysis. The empirical model shows that industry-, firmand e-commerce related variables, such as the entry of competing IPOs and the selling of digital products or services, can reduce an Internet firm’s hazard rate. I...

It is somewhat true that in most mainstream statistical literature the transition from inference to a formal decision model is seldom explicitly considered. Since the Markov chain Monte Carlo (MCMC) revolution in Bayesian statistics, focus has generally been on the development of novel algorithmic methods to enable comprehensive inference in a variety of applications, or to tackle realistic pro...

Date The final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline. The multiresolution estimator, originally a wavelet-based method for density estimation, was recently extended for estimation of hazard functions. The multiresolution hazard (MRH) metho...

Inmany practical situations, a parametric model cannot be expected to describe in an appropriate manner the chance mechanism generating an observed dataset, and unrealistic features of some common models could lead to unsatisfactory inferences. In these cases, we would like to relax parametric assumptions to allow greater modeling flexibility and robustness against misspecification of a paramet...

In this paper, we develop a Bayesian analysis of a semi-parametric binary choice model. The prior speciication of the functional parameter , namely the distribution function of a latent variable, is of the Dirichlet process type and the prior speciication of the Euclidean parameter , namely the coeecients of a linear combination of exogenous variables, is left arbitrary. The model identiication...

Limiting tail behavior of distributions are known to follow one of three possible limiting distributions, depending on the domain of attraction of the observational model under suitable regularity conditions. This work proposes a new approach for identification and analysis of the limiting regimes that these data exceedances belong to. The model-based approach uses a mixture at the observationa...

In public health management there is a need to produce subnational estimates of health outcomes. Often, however, funds are not available to collect samples large enough to produce traditional survey sample estimates for each subnational area. Although parametric hierarchical methods have been successfully used to derive estimates from small samples, there is a concern that the geographic divers...