Table of Contents
Advances in Statistics
Volume 2015, Article ID 525136, 11 pages
Research Article

Statistical Inference in Dependent Component Hybrid Systems with Masked Data

1Department of Mathematical Sciences, University of Texas at El Paso, El Paso, TX 79968, USA
2College of Mathematics and Science, Shanghai Normal University, Shanghai 200234, China
3Business Information Management School, Shanghai University of International Business and Economics, Shanghai 201600, China

Received 26 March 2015; Accepted 26 May 2015

Academic Editor: Shuo-Jye Wu

Copyright © 2015 Naijun Sha et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Complex systems are usually composed of simple hybrid systems. In this paper, we consider statistical inference for two fundamental hybrid systems: series-parallel and parallel-series systems based on masked data. Assuming dependent lifetimes of components modelled by Marshall and Olkin’s bivariate exponential distribution in the system, we present maximum likelihood and interval estimation of parameters of interest. Intensive simulation studies are performed to demonstrate the efficiency of the methods.