It is well known that, given observable data for a competing risk problem, there is always an independent model consistent with the data. It has been pointed out, however, that this independent model does not necessarily have to be one with proper marginals. One purpose of this paper is to...

Within reliability theory, identifiability problems arise through competing risks. If we have a series system of several components, and if that system is replaced or repaired to as good as new on failure, then the different component failures represent competing risks for the system. It is well...

This paper combines the use of (binary) logistic regression and stochastic frontier analysis to assess the operational effectiveness of the UK Coastguard (Maritime Rescue) coordination centres over the period 1995-1998. In particular, the rationale for the Government's decision - confirmed in...

The design, implementation and use of adequate performance measurement and management frameworks can play an important role if organisations are to succeed in an increasingly complex, interdependent and changing world. Yet, despite widespread recognition of the importance of performance...

Decisions during the reliability growth development process of engineering equipment involve trade-offs between cost and risk. However slight, there exists a chance an item of equipment will not function as planned during its specified life. Consequently the producer can incur a financial...

Much failure, and other event, data are commonly highly censored. Consequently this limits the efficacy of many statistical analysis techniques. The limited expected value (LEV) function presents an alternative way of characterizing lifetime distributions. In essence the LEV provides a means of...

Demands by clients for earlier delivery after a project has started are increasing. This paper investigates the consequential disruption and delay that follows from the contractor accepting these demands. Explorations are carried out using a System Dynamics model based upon a large model...

Fully Bayesian approaches to analysis can be overly ambitious where there exist realistic limitations on the ability of experts to provide prior distributions for all relevant parameters. This research was motivated by situations where expert judgement exists to support the development of prior...