Using an updated version of the CWS model (introduced by Eyckmans and Tulkens in Resource and Energy Economics 2003), this paper intends to evaluate with numbers the respective merits of two competing notions of coalition stability in the standard global public goods model as customarily applied...

Using an updated version of the CWS model (introduced by Eyckmans and Tulkens in Resource and Energy Economics 2003), this paper intends to evaluate with numbers the respective merits of two competing notions of coalition stability in the standard global public goods model as customarily applied...

The use of American style equity options as hedging instrument has gained currency in recent times. This phenomenon devolves from the ever-expanding need by individuals, corporations and governments to hedge away their financial risks and the clarion call for derivative securities that give the...

Basic methods to compute the required sample size are well understood and supported by widely available software. However, the sophistication of the sample size methods commonly used has not kept pace with the complexity of the experimental designs most often employed in practice. In this paper,...

Managers wish to verify that a particular engineering design meets their require- ments. This design's future environment will differ from the environment assumed during the design. Therefore it is crucial to determine which variations in the envi- ronment may make this design unacceptable. The...

Abstract: To analyze the input/output behavior of simulation models with multiple responses, we may apply either univariate or multivariate Kriging (Gaussian process) metamodels. In multivariate Kriging we face a major problem: the covariance matrix of all responses should remain positive-de...

This paper proposes a novel method to select an experimental design for interpolation in random simulation, especially discrete event simulation.(Though the paper focuses on Kriging, this design approach may also apply to other types of metamodels such as linear regression models.)Assuming that...

Optimization of simulated systems is the goal of many methods, but most methods as- sume known environments. We, however, develop a `robust' methodology that accounts for uncertain environments. Our methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques...

Abstract: This paper investigates two related questions: (1) How to derive a confidence interval for the output of a combination of simulation inputs not yet simulated? (2) How to select the next combination to be simulated when searching for the optimal combination? To answer these questions,...

This article uses a sequentialized experimental design to select simulation input com- binations for global optimization, based on Kriging (also called Gaussian process or spatial correlation modeling); this Kriging is used to analyze the input/output data of the simulation model (computer...