Bayesian interim analysis of lifetime data

Bayesian reliability analysis for fuzzy lifetime data

Lifetime data are important in reliability analysis. Classical reliability estimation is based on precise lifetime data. It is usually assumed that observed lifetime data are precise real numbers. However, some collected lifetime data might be imprecise and are represented in the form of fuzzy numbers. Thus, it is necessary to generalize classical statistical estimation methods for real numbers...

Bayesian interim statistical analysis of randomised trials.

Correspondence to: Dr James M Brophy (e-mail [email protected]) 33 Epstein SS, Ozonoff D. Leukemias and blood dyscrasias following exposure to chlordane and heptachlor. Teratog Carcinog Mutagen 1987; 7: 527–40. 34 Shindell S, Ulrich S. Mortality of workers employed in the manufacture of chlordane: an update. J Occup Med 1986; 28: 497–501. 35 Brown DP. Mortality of workers employed at orga...

Bayesian Prediction in Spatial Data Analysis

Bayesian Analysis of Survival Data with Spatial Correlation

Often in practice the data on the mortality of a living unit correlation is due to the location of the observations in the study‎. ‎One of the most important issues in the analysis of survival data with spatial dependence‎, ‎is estimation of the parameters and prediction of the unknown values in known sites based on observations vector‎. ‎In this paper to analyze this type of survival‎, ‎Cox...

Bayesian Two-Sample Prediction with Progressively Type-II Censored Data for Some Lifetime Models

Prediction on the basis of censored data is very important topic in many fields including medical and engineering sciences. In this paper, based on progressive Type-II right censoring scheme, we will discuss Bayesian two-sample prediction. A general form for lifetime model including some well known and useful models such asWeibull and Pareto is considered for obtaining prediction bounds ...