A variety of shrinkage methods for estimating unknown parameters has been considered. We derive and compare the shrinkage estimators for the reliability function of the two-parameter exponential distribution. Simulation experiments are used to study the performances of these estimators.
In this paper a variety of shrinkage methods for estimating unknown population parameters has been considered. Aprior distribution for the parameters around their natural origins has been postulated and the ordinary Bayes estimators are used in place of natural origins in the ordinary shrinkage estimators to obtain Bayesian shrinkage estimators. The results are applied to the problem of estimating the location and scale parameters and the reliability function of the two-parameter exponential distribution. Simulation experiments are used to study the performances of these estimators.
Communication protocols are often investigated using simulation. This paper presents a performance study of the distributed coordination function of 802.11 networks. Firstly, our study illustrates the different classes of Petri Nets used for modeling network protocols and their robustness in modeling based on formal methods. Next we propose a detailed 802.11b model based on Object-oriented Petri Nets that precises backoff procedure and time synchronization. Then, performance analyses are evaluated by simulation for a dense wireless network and compared with other measurements approaches. Our main goal is to propose a modular model that will enable to evaluate the impact of network performances on the performances of distributed discrete event systems.