Modeling and Analysis of Engineering Systems Data Using Flowgraph Models

An innovative approach to data analysis for complicated stochastic systems involves modeling based on flowgraph methods. This article introduces flowgraph and associated saddlepoint methods for problems in systems engineering and reliability. The methods are especially useful for analyzing time-to-event data and finding predictive distributions of such data. Applications to a cellulartelephone network are given. Advantages of flowgraph models over direct simulation are presented. Methods of likelihood construction for incomplete data are given.