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Limit Theory for Performance Modeling of Future Event Set Algorithms
Limit Theory Performance Modeling Future Event Set Algorithms
2015/7/8
In a discrete-event simulation, the information related to the events scheduled to occur in the future is kept in a data structure called the future event set (FES). In this paper, we study the intera...
Can the Regenerative Method be Applied to Discrete-Event Simulations?
Regenerative Method Applied Discrete-Event Simulations
2015/7/8
The regenerative method enjoys asymptotic properties that make it a highly desirable approach for steady-state simulation output analysis. It has been shown that virtually all discrete-event simulatio...
Energy consumption of electronic devices has become a serious concern in recent years. Power management (PM) algorithms aim at reducing energy consumption at the system-level by selectively placing co...
Regenerative Steady-State Simulation of Discrete-Event Systems
Regenerative Steady-State Simulation Discrete-Event Systems
2015/7/8
The regenerative method possesses certain asymptotic properties that dominate those of other steady-state simulation output analysis methods, such as batch means. Therefore, applying the regenerative ...
Rare-Event Simulation for Infinite Server Queues
Rare-Event Simulation Infinite Server Queues
2015/7/8
We discuss rare-event simulation methodology for computing tail probabilities for infinite-server queues. Our theoretical discussion also offers some new simulation insights into the change-of-measure...
On the Validity of Long-Run Estimation Methods for Discrete-Event Systems
Validity Long-Run Estimation Methods Discrete-Event Systems
2015/7/8
On the Validity of Long-Run Estimation Methods for Discrete-Event Systems.
Much of the rare-event simulation literature is concerned with the development of asymptotically optimal algorithms. Because of the difficulties associated with applying these ideas to complex models,...
Efficient Rare-event Simulation for the Maximum of Heavy-tailed Random Walks
State-dependent importance sampling rare-event simulation heavy-tails Lyapunov bounds random walks
2015/7/6
Let (Xn: n ≥ 0) be a sequence of i.i.d. r.v.’s with negative mean. Set S0 = 0 and define Sn = X1 +· · ·+Xn. We propose an importance sampling algorithm to estimate the tail of M = max{Sn: n ≥ 0} that ...
Rare Event Simulation for a Generalized Hawkes Process
Rare Event Simulation Generalized Hawkes Process
2015/7/6
In this paper we study rare event simulation for the tail probability of an affine point process (Jt)t≥0 that generalizes the Hawkes process. By constructing a suitable exponential martingale, we are ...
Asymptotic Robustness of Estimators in Rare-Event Simulation
Asymptotic Robustness Estimators Rare-Event Simulation
2015/7/6
The asymptotic robustness of estimators as a function of a rarity parameter, in the context of rare-event simulation, is often qualified by properties such as bounded relative error (BRE) and logarith...
Combining Dynamic Predictions from Joint Models for Longitudinal and Time-to-Event Data using Bayesian Model Averaging
Prognostic Modeling Risk Prediction
2013/4/27
The joint modeling of longitudinal and time-to-event data is an active area of statistics research that has received a lot of attention in the recent years. More recently, a new and attractive applica...
Rare event simulation for processes generated via stochastic fixed point equations
Monte Carlo methods importance sampling perpetuities
2011/7/19
In a number of applications, particularly in financial and actuarial mathematics, it is of interest to characterize the tail distribution of a random variable V satisfying the distributional equation ...
Distributed Detection/Isolation Procedures for Quickest Event Detection in Large Extent Wireless Sensor Networks
Disorder problem distributed quickest change detection detection with distance dependent sensing fusion of CUSUMs multi–hypothesis change detection
2011/6/20
We study a problem of distributed detection of an event in a large extent wireless sensor network
(WSN), where the event influences the observations of the sensors only in the vicinity of where it oc...
HIV dynamics and natural history studies: Joint modeling with doubly interval-censored event time and infrequent longitudinal data
AIDS antiviral treatment interval censoring semiparametric regression
2011/6/16
Hepatitis C virus (HCV) coinfection has become one of the most
challenging clinical situations to manage in HIV-infected patients.
Recently the effect of HCV coinfection on HIV dynamics following
i...
Modelling time to event with observations made at arbitrary times
Modelling observations RAFT RPH
2011/3/21
We introduce new methods of analysing time to event data via extended versions of the proportional hazards and accelerated failure time (AFT) models. In many time to event studies, the time of first o...