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A new class of strongly consistent variance estimators for steady-state simulations
- Source :
- Stochastic Processes and their Applications. 28:71-80
- Publication Year :
- 1988
- Publisher :
- Elsevier BV, 1988.
-
Abstract
- The principal problem associated with steady-state simulation is the estimation of the variance term in an associated central limit theorem. This paper develops several strongly consistent estimates for this term using the strong approximations available for Brownian motion. A comparison of rates of convergence is given for a variety of estimators.
- Subjects :
- Statistics and Probability
regenerative simulation
Stochastic process
strong approximation laws
Applied Mathematics
Estimator
rates of convergence
Variance (accounting)
Term (time)
simulation output analysis
Modelling and Simulation
strongly consistent estimation
Modeling and Simulation
Consistent estimator
Convergence (routing)
Econometrics
Applied mathematics
Brownian motion
confidence intervals
steady-state simulation
Mathematics
Central limit theorem
Subjects
Details
- ISSN :
- 03044149
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- Stochastic Processes and their Applications
- Accession number :
- edsair.doi.dedup.....853cf4e29343c064e666b5b6674dcb77
- Full Text :
- https://doi.org/10.1016/0304-4149(88)90065-8