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Type of Document Dissertation Author Lada, Emily Kate, URN etd-04032003-141616 Title A Wavelet-Based Procedure for Steady-State Simulation Output Analysis Degree PhD Graduate Program Operations Research Advisory Committee
Advisor Name Title James R. Wilson Committee Chair Charles E. Smith Committee Member David Goldsman Committee Member Elmor Peterson Committee Member Stephen D. Roberts Committee Member Keywords
- Simulation
- Wavelets
- Spectral Analysis
- Output Analysis
Date of Defense 2003-03-31 Availability unrestricted Abstract The objective of this research is to develop an automated sequentialprocedure by which an asymptotically valid confidence interval is
constructed for the steady-state mean of a simulation output process.
This procedure, called WASSP, determines a batch size and a warm-up
period beyond which the computed batch means constitute an
approximately stationary Gaussian process. WASSP then uses wavelets to
approximate the log of the smoothed periodogram of the batch means
process, from which an estimate of the steady-state variance constant
(SSVC) of the original (unbatched) process is obtained. Together with
a sample mean that has been suitably truncated to eliminate
initialization bias, the SSVC estimator is used to construct a
reliable confidence-interval estimator of the steady-state mean that
satisfies a user-specified absolute or relative precision requirement.
An extensive performance evaluation includes testing WASSP on a suite
of processes that include extreme examples of the warm-up and
correlation problems. The results indicate that WASSP is successful in
detecting and eliminating initialization bias as well as in
constructing an approximately stationary process so that an
asymptotically valid confidence interval for the steady-state mean can
be generated even if the original process is highly correlated and has
a pronounced initial transient period. Furthermore, the performance
evaluation also includes a comparison of WASSP to other methods for
steady-state output analysis. The results indicate that WASSP is in
general a more robust procedure than the other methods, and we believe
that WASSP represents an advance in spectral methods for steady-state
output analysis.
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