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作者：Milstein, GN; Tretyakov, MV
作者单位：Leibniz Association; Weierstrass Institute for Applied Analysis & Stochastics; Ural Federal University
摘要：Mean-square approximations, which ensure boundedness of both time and space increments, are constructed for stochastic differential equations in a bounded domain. The proposed algorithms are based on a space-time discretization using a random walk over boundaries of small space-time parallelepipeds. To realize the algorithms, exact distributions for exit points of the space-time Brownian motion from a space-time parallelepiped are given. Convergence theorems are stated for the proposed algorit...
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作者：Resnick, S; Samorodnitsky, G; Xue, F
作者单位：Cornell University; Cornell University
摘要：For the stable moving average process X-t = integral(-infinity)(infinity) f(t + x) M(dx), t= 1,2,...., we find the weak limit of its sample autocorrelation function as the sample size n increases to infinity. It turns out that, as a rule, this limit is random! This shows how dangerous it is to rely on sample correlation as a model fitting tool in the heavy tailed case. We discuss for what functions f this limit is nonrandom for all (or only some-this can be the case, too!) lags.
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作者：Bramson, M
作者单位：University of Minnesota System; University of Minnesota Twin Cities
摘要：Fluid models have become a standard tool for demonstrating stability for queueing networks. It is presently not known, however, when the stability of a fluid model follows from that of the corresponding queueing network. We present an example of a queueing network where such stability does not, in fact, follow This example also shows that the behavior of the fluid limits and the fluid model solutions for the same queueing network can differ considerably from one another.
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作者：Fannjiang, A; Komorowski, T
作者单位：University of California System; University of California Davis; Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：We prove turbulent diffusion theorems for Markovian velocity fields which either are mixing in time or have stationary vector potentials.
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作者：Piau, D
作者单位：Universite Claude Bernard Lyon 1
摘要：We prove a large deviations principle for the Young measures of a stochastic homogenization model of Poissonian biphased material.
