We propose a novel Bayesian model framework for discrete ordinal and count data based on conditional transformations of the responses. The transformation function is estimated from in conjunction with an priori chosen reference distribution. For responses, resulting sense that it fully parametric yet distribution-free approach can additionally account excess zeros additive specifications. categ...

Abstract We introduce a new definition of bubbles in discrete-time models based on the discounted stock price losing mass under an equivalent martingale measure at some finite drawdown. provide probabilistic characterisations this and give examples martingales that are others not. In Markovian case, we sufficient analytic conditions for presence bubbles. also show existence is directly linked t...

Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The prop...

In recent years, formal methods have been used as an important tool for performance evaluation and verification of a wide range of systems. In the view points of engineers and practitioners, however, there are still some major difficulties in using formal methods. In this paper, we introduce a new formal modeling language to fill the gaps between object-oriented programming languages (OOPLs) us...