Add to ORKGAbstract: 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 paper we describe a method for estimating time evolution of several quantiles within some time interval. It is based on independent replications and its capability is demonstrated by simulating processes with different kinds of stationary, non-stationary or transient behaviour
This paper proposes a technique for estimating steady-state quantiles from discrete-event simu-latio...
We look at numerical methods for simulation of stochastic differential equations exhibiting volatili...
We present a general framework for applying simulation to optimize the behavior of discrete event sy...
Discrete event simulation is well known to be a powerful approach to investigate behaviour of comple...
Simulation output data analysis in performance evaluation studies of complex stochastic systems such...
Simulation results are often limited to mean values, even though this provides very limited informat...
ABSTRACT The issue of the initial transient phase in steady state simulation has been widely discuss...
Quantiles are convenient measures of the entire range of values of simulation outputs. However, unli...
This paper proposes a technique for estimating steady-state quantiles from discrete-event simulation...
The credibility of the final results from stochastic simulation has had limited discussion in the si...
Simulation results are often limited to mean values, even though this provides very limited infor- m...
A time-varying quantile can be fitted to a sequence of observations by formulating a time series mod...
We propose nonstandard simulation estimators of expected time averages over finite intervals [0, t],...
In both modern stochastic analysis and more traditional probability and statistics, one way of chara...
The first idea of a methodology able to study the MSPE evolution in replicated runs got out thanks t...
This paper proposes a technique for estimating steady-state quantiles from discrete-event simu-latio...
We look at numerical methods for simulation of stochastic differential equations exhibiting volatili...
We present a general framework for applying simulation to optimize the behavior of discrete event sy...
Discrete event simulation is well known to be a powerful approach to investigate behaviour of comple...
Simulation output data analysis in performance evaluation studies of complex stochastic systems such...
Simulation results are often limited to mean values, even though this provides very limited informat...
ABSTRACT The issue of the initial transient phase in steady state simulation has been widely discuss...
Quantiles are convenient measures of the entire range of values of simulation outputs. However, unli...
This paper proposes a technique for estimating steady-state quantiles from discrete-event simulation...
The credibility of the final results from stochastic simulation has had limited discussion in the si...
Simulation results are often limited to mean values, even though this provides very limited infor- m...
A time-varying quantile can be fitted to a sequence of observations by formulating a time series mod...
We propose nonstandard simulation estimators of expected time averages over finite intervals [0, t],...
In both modern stochastic analysis and more traditional probability and statistics, one way of chara...
The first idea of a methodology able to study the MSPE evolution in replicated runs got out thanks t...
This paper proposes a technique for estimating steady-state quantiles from discrete-event simu-latio...
We look at numerical methods for simulation of stochastic differential equations exhibiting volatili...
We present a general framework for applying simulation to optimize the behavior of discrete event sy...