The Annals of Applied Probability

最新文章

• INSENSITIVITY IN DISCRETE-TIME GENERALIZED SEMI-MARKOV PROCESSES ALLOWING MULTIPLE EVENTS AND PROBABILISTIC SERVICE SCHEDULING AI翻译
  作者：Henderson, W.; Pearce, C. E. M.; Taylor, P. G.; van Dijk, N. M.
  作者单位：University of Adelaide; Vrije Universiteit Amsterdam
  摘要：In this paper we treat a discrete-time generalized semi-Markov process in which simultaneous deaths of more than one lifetime and simultaneous arrivals are permitted and service scheduling is probabilistic. Necessary and sufficient conditions for insensitivity are derived and a simple algorithmic procedure provided whereby the equilibrium probabilities can be furnished when insensitivity holds. Some particular cases of special interest are examined in detail.
• ON WEAK CONVERGENCE OF CONDITIONAL SURVIVAL MEASURE OF ONE-DIMENSIONAL BROWNIAN MOTION WITH A DRIFT AI翻译
  作者：Povel, Tobias
  作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
  摘要：We consider a one-dimensional Brownian motion with a constant drift, moving among Poissonian obstacles. In the case where the drift is below some critical value we characterize the limiting distribution of the process under the conditional probability measure that the particle has survived up to time t. Unlike the situation where the drift equals zero, we show in particular that in the presence of a constant drift, the process in natural scale feels the boundary.
• PREDICTION AND NON-GAUSSIAN AUTOREGRESSIVE STATIONARY SEQUENCES AI翻译
  作者：Rosenblatt, Murray
  作者单位：University of California System; University of California San Diego
  摘要：The object of this paper is to show that under certain auxiliary assumptions a stationary autoregressive sequence has a best predictor in mean square that is linear if and only if the sequence is minimum phase or is Gaussian when all moments are finite.
• EFFICIENT MONTE CARLO SIMULATION OF SECURITY PRICES AI翻译
  作者：Duffie, Darrell; Glynn, Peter
  作者单位：Stanford University; Stanford University
  摘要：This paper provides an asymptotically efficient algorithm for the allocation of computing resources to the problem of Monte Carlo integration of continuous-time security prices. The tradeoff between increasing the number of time intervals per unit of time and increasing the number of simulations, given a limited budget of computer time, is resolved for first-order discretization schemes (such as Euler) as well as second- and higher-order schemes (such as those of Milshtein or Talay).
• DIFFUSION APPROXIMATION FOR OPEN STATE-DEPENDENT QUEUEING NETWORKS IN THE HEAVY TRAFFIC SITUATION AI翻译
  作者：Yamada, Keigo
  作者单位：Kanagawa University
  摘要：We consider open queueing networks in which arrival and service rates are dependent on the state (i.e., queue length) of the network. They are modeled as multidimensional birth and death processes. If a heavy traffic condition is satisfied on the behavior of arrival and service rates when the queue length becomes very large, it is shown that a properly normalized sequence of queue length converges in law to a reflecting diffusion process.
• ON THE LOCAL TIME OF THE BROWNIAN MOTION AI翻译
  作者：Takacs, Lajos
  作者单位：University System of Ohio; Case Western Reserve University
  摘要：In this paper explicit formulas are given for the distribution function, the density function and the moments of the local time of the reflecting Brownian motion process.
• DYNAMIC SCHEDULING WITH CONVEX DELAY COSTS: THE GENERALIZED cμ RULE AI翻译
  作者：van Mieghem, Jan A.
  作者单位：Stanford University
  摘要：We consider a general single-server multiclass queueing system that incurs a delay cost C-k(tau(k)) for each class k job that resides tau(k) units of time in the system. This paper derives a scheduling policy that minimizes the total cumulative delay cost when the system operates during a finite time horizon. Denote the marginal delay cost function and the (possibly nonstationary) average processing time of class k by c(k) = C'(k) and 1/mu(k), respectively, and let a(k)(t) be the age or time t...
• RATES OF CONVERGENCE FOR THE MOVE-TO-ROOT MARKOV CHAIN FOR BINARY SEARCH TREES AI翻译
  作者：Dobrow, Robert P.; Fill, James Allen
  作者单位：Johns Hopkins University; National Institute of Standards & Technology (NIST) - USA
  摘要：The move-to-root heuristic is a self-organizing rule that attempts to keep a binary search tree in near-optimal form. It is a tree analogue of the move-to-front scheme (also known as the weighted random-to-top card shuffle or Tsetlin library) for self-organizing lists. We study convergence of the move-to-root Markov chain to its stationary distribution and show that move-to-root converges two to four times faster than move-to-front for many examples. We also discuss asymptotics for expected se...
• ASYMPTOTIC ANALYSIS OF TAIL PROBABILITIES BASED ON THE COMPUTATION OF MOMENTS AI翻译
  作者：Abate, Joseph; Choudhury, Gagan L.; Lucantoni, David M.; Whitt, Ward
  作者单位：Nokia Corporation; Nokia Bell Labs; AT&T
  摘要：Choudhury and Lucantoni recently developed an algorithm for calculating moments of a probability distribution by numerically inverting its moment generating function. They also showed that high-order moments can be used to calculate asymptotic parameters of the complementary cumulative distribution function when, an asymptotic form is assumed, such as F-c(x) similar to alpha x(beta) e (-eta x) as x -> infinity. Moment-based algorithms for computing asymptotic parameters are especially useful w...
• LEVY BANDITS: MULTI-ARMED BANDITS DRIVEN BY LEVY PROCESSES AI翻译
  作者：Kaspi, Haya; Mandelbaum, Avi
  作者单位：Technion Israel Institute of Technology
  摘要：Levy bandits are multi-armed bandits driven by Levy processes. As anticipated from existing research, Levy bandits are optimally controlled by an index strategy: One can associate with each arm an index function of its state, and optimal strategies are those that allocate time to arms whose states have the largest index. Furthermore, the index function of an arm is calculated independently of the other arms, and the optimal reward can be expressed in terms of the indices. Somewhat less anticip...