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arXiv 1205.5083math.PR
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约束扩散不变分布的一个数值格式

A Numerical Scheme for Invariant Distributions of Constrained Diffusions

Amarjit Budhiraja, Jiang Chen, Sylvain Rubenthaler

摘要:

多面体区域中的反射扩散常用作高负荷服务中随机处理网络的近似模型。这种模型的平稳分布给出了相应随机网络的稳态性能的有用信息,因此,重要的是开发可靠和有效的算法用于这种分布的数值计算。在这项工作中,我们提出并分析了一个Monte-Carlo计划的基础上的欧拉型离散的反射随机微分方程使用一个单一的序列的时间离散步骤,减少到零的时间接近无穷大。适当加权的经验措施,从模拟的离散化反射扩散的近似不变的概率测度的真实扩散模型。几乎必然一致性结果的建立,特别是表明,加权平均多项式增长的连续泛函上的离散模拟系统收敛a.s.关于不变测度的相应积分。证明依赖于构造合适的李雅普诺夫函数的紧密性和一致的可积性和特征几乎必然极限点通过扩展Echeverria的标准反射扩散。Skorohod问题的正则性在证明中起着关键作用。对于合适的检验函数族,也得到了收敛速度。蒙特卡罗方法的一个主要优点是易于实现,特别是对于高维问题。一个八维Skorohod问题的数值例子来说明该方法的适用性。

英文摘要:

Reflected diffusions in polyhedral domains are commonly used as approximate models for stochastic processing networks in heavy traffic. Stationary distributions of such models give useful information on the steady state performance of the corresponding stochastic networks and thus it is important to develop reliable and efficient algorithms for numerical computation of such distributions. In this work we propose and analyze a Monte-Carlo scheme based on an Euler type discretization of the reflected stochastic differential equation using a single sequence of time discretization steps which decrease to zero as time approaches infinity. Appropriately weighted empirical measures constructed from the simulated discretized reflected diffusion are proposed as approximations for the invariant probability measure of the true diffusion model. Almost sure consistency results are established that in particular show that weighted averages of polynomially growing continuous functionals evaluated on the discretized simulated system converge a.s. to the corresponding integrals with respect to the invariant measure. Proofs rely on constructing suitable Lyapunov functions for tightness and uniform integrability and characterizing almost sure limit points through an extension of Echeverria's criteria for reflected diffusions. Regularity properties of the underlying Skorohod problems play a key role in the proofs. Rates of convergence for suitable families of test functions are also obtained. A key advantage of Monte-Carlo methods is the ease of implementation, particularly for high dimensional problems. A numerical example of a eight dimensional Skorohod problem is presented to illustrate the applicability of the approach.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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