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Stochastic decompositions in bivariate risk and queueing models with mutual assistance

机译:双方辅助的互联风险和排队模型的随机分解

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We consider two bivariate models with two-way interactions in context of risk and queueing theory. The two entities interact with each other by providing assistance but otherwise evolve independently. We focus on certain random quantities underlying the joint survival probability and the joint stationary workload, and show that these admit stochastic decomposition. Each one can be seen as an independent sum of respective quantities for the two models with one-way interaction. Additionally, we discuss a rather general method of establishing decompositions from a given kernel equation by identifying two independent random variables from their difference, which may be useful for other models. Finally, we point out that the same decomposition is true for uncorrelated Brownian motion reflected to stay in a quadrant, and it concerns the face measures appearing in the basic adjoint relationship.
机译:我们在风险和排队理论中考虑两个具有双向相互作用的两种双向互动。 这两个实体通过提供援助来互相互动,但以其他方式独立发展。 我们专注于联合生存概率和联合静止工作量的某些随机量,并表明这些承认随机分解。 每个具有单向交互的两个模型可以被视为各个数量的独立和。 另外,我们讨论一种相当一般的方法,通过识别来自它们的差异的两个独立随机变量来建立来自给定内核方程的分解,这可能对其他模型有用。 最后,我们指出的是,对于反射以保持象限的不相关的布朗运动,相同的分解是正确的,并且它涉及出现在基本伴随关系中的面部措施。

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