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In steady-state simulation the output data of the transient phase often causes a bias in the estimation of the steadystate results. A common advice is to cut off this transient phase. Finding an appropriate truncation point is a wellknown problem and is still not completely solved. In this paper we consider two algorithms for the determination of the… (More)

Stochastic simulation has become a well established paradigm used in performance evaluation of various complex dynamic systems. Most simulation output analysis is confined to the estimation of mean values. This is true for both finite horizon and steady state simulation. The estimation of quantiles provides a deeper insight into the simulated model. In this… (More)

- Mirko Eickhoff, Donald C. McNickle, Krzysztof Pawlikowski
- VALUETOOLS
- 2007

The issue of the initial transient phase in steady state simulation has been widely discussed in simulation literature. Many methods have been proposed for deciding the duration of this phase of simulation, to determine a valid truncation point of the transient portion of output data. However, practically all these methods can only be used in simulations… (More)

For simulation output the estimation of several quantiles usually provides a deeper insight than mean value analysis. So far, quantile estimation has usually been applied to show the long run behaviour of a system. In this paper we describe a method to depict several quantiles over simulation time to show the transient behaviour. This method is based on… (More)

This paper describes an extension of the replication/deletion approach for removal of the initialisation bias in the output data of discrete-event simulations. The proposed extension adaptively determines the cutoff index and also respects a user given ratio between the lengths of transient and steadystate period. We show the benefits of the extension… (More)

- Mirko Eickhoff, Donald C. McNickle, Krzysztof Pawlikowski
- VALUETOOLS
- 2007

Simulation output data analysis in performance evaluation studies of complex stochastic systems such as the Internet is typically limited to mean values, even though it provides very limited information about the analysed system's performance. Quantile analysis is not as common, even though it can provide much deeper insights into the system of interest. A… (More)

- Mirko Eickhoff
- MMB
- 2006

Steady state simulation is used to study long-run behavior. Usually only the expected value of the steady state probability distribution function is estimated. In many cases quantiles of this distribution are of higher interest. In this paper a new usage of quantile estimators is proposed, which is derived from mean value analysis and is based on multiple… (More)

- Falko Bause, Mirko Eickhoff
- Winter Simulation Conference
- 2003

In steady-state simulation the output data of the transient phase often causes a bias in the estimation of the steady-state results. A common advice is to cut off this transient phase. Finding an appropriate truncation point is a well-known problem and is still not completely solved. In this paper we consider two algorithms for the determination of the… (More)

Simulation results are often limited to mean values, even though this provides very limited information about the analyzed systems’ performance. Quantile analysis provides much deeper insights into the performance of simulation system of interest. A set of quantiles can be used to approximate a cumulative distribution function, providing full information… (More)

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