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21.
Jeannette H. C. Woerner 《商业与工业应用随机模型》2005,21(1):27-44
In the framework of stochastic volatility models we examine estimators for the integrated volatility based on the pth power variation (i.e. the sum of pth absolute powers of the log‐returns). We derive consistency and distributional results for the estimators given high‐frequency data, especially taking into account what kind of process we may add to our model without affecting the estimate of the integrated volatility. This may on the one hand be interpreted as a possible flexibility in modelling, for example adding jumps or even leaving the framework of semimartingales by adding a fractional Brownian motion, or on the other hand as robustness against model misspecification. We will discuss possible choices of p under different model assumptions and irregularly spaced data. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
22.
We consider the optimal service control of a multiclass M/G/1 queueing system in which customers are served nonpreemptively and the system cost rate is additive across classes and increasing convex in the numbers present in each class. Following Whittle's approach to a class of restless bandit problems, we develop a Langrangian relaxation of the service control problem which serves to motivate the development of a class of index heuristics. The index for a particular customer class is characterised as a fair charge for service of that class. The paper develops these indices and reports an extensive numerical investigation which exhibits strong performance of the index heuristics for both discounted and average costs. 相似文献
23.
Miklós Csörgő 《Periodica Mathematica Hungarica》2005,50(1-2):1-27
Summary This article provides a glimpse of some of the highlights of the joint work of Endre Csáki and Pál Révész since 1979. The topics of this short exploration of the rich stochastic milieu of this inspiring collaboration revolve around Brownian motion, random walks and their long excursions, local times and additive functionals, iterated processes, almost sure local and global central limit theorems, integral functionals of geometric stochastic processes, favourite sites--favourite values and jump sizes for random walk and Brownian motion, random walking in a random scenery, and large void zones and occupation times for coalescing random walks. 相似文献
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用Quantum Sutton-Chen多体势对Ag6Cu4和CuNi液态金属凝固过程进行了分子动力学模拟研究.在冷却速率2×1012到2×1014K/s范围内,CuNi总是形成fcc晶体结构,而Ag6Cu4总是形成非晶态结构.考虑到CuNi及AgCu中原子半径之比分别为1.025和1.13,那么模拟结果证实了原子的尺寸差别是非晶态合金形成的一个主要影响因素.此外采用键对及原子多面体类型指数法对凝固过程中微观结构组态变化的分析,不但能说明二十面体结构在非晶态合金形成和稳定性中所起的关键作用,又有助于对液态金属的凝固过程、非晶态结构特征的深入理解. 相似文献
26.
M/G/1非空竭服务休假排队系统随机分解的简化算法 总被引:2,自引:0,他引:2
本文根据M/G/1非空竭服务休假排队系统稳态队长随机分解的结构特征提出一种统一算法,该方法简洁高效,避免了再生循环方法繁杂的运算。运用该方法得出的结果与已知的用再生循环方法得出的结论一致。并且修正了Levy(1989)关于Bernoulli闸门服务休假排队系统随机分解的一个错误。 相似文献
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We introduce here some Itô calculus for non-continuous Dirichlet processes. Such calculus extends what was known for continuous Dirichlet processes or for semimartingales. In particular we prove that non-continuous Dirichlet processes are stable under C
1 transformation. 相似文献
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The Sample Average Approximation Method Applied to Stochastic Routing Problems: A Computational Study 总被引:1,自引:0,他引:1
Bram Verweij Shabbir Ahmed Anton J. Kleywegt George Nemhauser Alexander Shapiro 《Computational Optimization and Applications》2003,24(2-3):289-333
The sample average approximation (SAA) method is an approach for solving stochastic optimization problems by using Monte Carlo simulation. In this technique the expected objective function of the stochastic problem is approximated by a sample average estimate derived from a random sample. The resulting sample average approximating problem is then solved by deterministic optimization techniques. The process is repeated with different samples to obtain candidate solutions along with statistical estimates of their optimality gaps.We present a detailed computational study of the application of the SAA method to solve three classes of stochastic routing problems. These stochastic problems involve an extremely large number of scenarios and first-stage integer variables. For each of the three problem classes, we use decomposition and branch-and-cut to solve the approximating problem within the SAA scheme. Our computational results indicate that the proposed method is successful in solving problems with up to 21694 scenarios to within an estimated 1.0% of optimality. Furthermore, a surprising observation is that the number of optimality cuts required to solve the approximating problem to optimality does not significantly increase with the size of the sample. Therefore, the observed computation times needed to find optimal solutions to the approximating problems grow only linearly with the sample size. As a result, we are able to find provably near-optimal solutions to these difficult stochastic programs using only a moderate amount of computation time. 相似文献