What is it about?
We present aymptotically valid methods to remove the initial transient that typically arises in the estimation of steady-state performace measures from the output of simulation experiments. We provide empirical evidence that these methods perform better than previously proposed methodologies.
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Why is it important?
The estimation of steady-state performance measures from the output of simulation experiments is very useful for validation of simulation codes, the study of continuous flow processes and Bayesian forecasting using Markov Chain Monte Carlo, among others. Removing initial transient typically improve the quallty of steady-state estimators.
Perspectives
Removing initial transient in steady-state simulation is a classical problem in steady-state simulation and this article proposes an interesting solution to this problem.
Dr. David Fernando Muñoz
Instituto Tecnologico Autonomo de Mexico
Read the Original
This page is a summary of: Empirical evaluation of initial transient deletion rules for the steady-state mean estimation problem, Computational Statistics, July 2022, Springer Science + Business Media,
DOI: 10.1007/s00180-022-01243-2.
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