around hydro conditions, market prices and river operations for fish recovery. In order to provide a high probability of …, BPA identifies key risks, models their relationships, and then analyzes their impacts on net revenues (total revenues less … expenses). BPA subsequently evaluates in the ToolKit Model the Treasury Payment Probability (TPP) resulting from the rates …

independent variables and models become more detailed and physics/engineering based. On the contrary, at higher levels, various … and/or discrete, analytic and/or computer models. These models are supposed to be deterministic (e.g. dynamics as ruled by … certain probability distribution function (PDF). Upon many realizations of the model, one can get reliable information about …

Risk is the product of the probability and consequences of an event. Both of these must be based upon sound science … integrated risk assessment. In this framework the underlying scientific understanding of processes that affect probability and … greatest level of uncertainty at the decision level. We review two examples of the determination of volcanic event probability …

modeling, and (3) discusses the differences in human error probability estimates arising from cultural differences. …

nodes representing random variables and directed edges indicating causality between variables. Each node has a probability …

-cause failure models have limitations in a simulation environment. In addition, substantial subjectivity is associated with … estimate parameters in traditional common-cause failure models. Simulation examples are presented for failures in time. The … redundancy and diversity of equipment in an effort to lower the probability of failure and therefore risk. However, it has long …

as a winning strategy even though the probability analysis shows that such a perception is incorrect. The simulation …Teaching probability can be challenging because the mathematical formulas often are too abstract and complex for the … example, the game of roulette can be an exciting application for teaching probability concepts. In this paper, we implement a …

performing computations in these models. This paper develops, analyzes, and evaluates two simulation algorithms for intensity … Zeevi, stochastic models and simulation.</i> …Dynamic, intensity-based point process models are widely used to measure and price the correlated default risk in …

, as is common in the literature. <i>This paper was accepted by Assaf Zeevi, stochastic models and simulation.</i> …Sequential sampling problems arise in stochastic simulation and many other applications. Sampling is used to infer the …