Waiting time paradox applied to transient times

Waiting time paradox applied to transient times

When working with chaotic systems, the average length of a transient phase before a particular event occurs is often required. Examples of this include the transient phase before a control mechanism can be activated @1,2# or the length of a chaotic transient after a crisis has occurred @3#. In both cases, the transient occurs before iterates fall into a small region. For controlling chaos, this...

Estimating Waiting times with the Time-varying Little’s Law

When waiting times cannot be observed directly, Little’s law can be applied to estimate the average waiting time by the average number in system divided by the average arrival rate, but that simple indirect estimator tends to be biased significantly when the arrival rates are timevarying and the service times are relatively long. Here it is shown that the bias in that indirect estimator can be ...

Latent Waiting Time Models For Bivariate Event Times With Censoring

Multivariate event time data arises frequently in both medical and industrial settings. In such data sets: event times may be associated with quite diierent occurrences, event times can not be considered as independent-the distribution of time to occurrence of one event may change after the occurrence of another, events can occur simultaneously, available covariate information may provide usefu...

Relative entropy and waiting times for continuous-time Markov processes

For discrete-time stochastic processes, there is a close connection between return/waiting times and entropy. Such a connection cannot be straightforwardly extended to the continuous-time setting. Contrarily to the discrete-time case one does need a reference measure and so the natural object is relative entropy rather than entropy. In this paper we elaborate on this in the case of continuous-t...

queuing theory to decrease waiting times in emergency department