This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Lada, E. K. Articles by Joines, J. A. Search for Related Content

Performance of a Wavelet-Based Spectral Procedure for Steady-State Simulation Analysis

SAS Institute, 100 SAS Campus Drive, Cary, North Carolina 27513-8617, USA
Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Campus Box 7906, Raleigh, North Carolina 27695-7906, USA
Maine Business School, University of Maine, Orono, Maine 04469-5723, USA
Department of Textile Engineering, Chemistry, and Science, North Carolina State University, Raleigh, North Carolina 27695-8301, USA
emily.lada{at}sas.com
jwilson{at}ncsu.edu
nsteiger{at}maine.edu
jeffjoines{at}ncsu.edu

A summary and an analysis are given for an experimental performance evaluation of WASSP, an automated wavelet-based spectral method for constructing an approximate confidence interval on the steady-state mean of a simulation output process such that the delivered confidence interval satisfies user-specified requirements on absolute or relative precision as well as coverage probability. The experimentation involved three difficult test problems, each with an output process exhibiting some combination of the following characteristics: a long warm-up period, a persistent autocorrelation structure, or a highly nonnormal marginal distribution. These problems were used to compare the performance of WASSP with that of the Heidelberger-Welch algorithm and ASAP3, two sequential procedures based respectively on the methods of spectral analysis and nonoverlapping batch means. Concerning efficiency (required sample sizes) and robustness against the statistical anomalies commonly encountered in simulation studies, WASSP outperformed the Heidelberger-Welch procedure and compared favorably with ASAP3.

Key words: simulation; statistical analysis; spectral analysis; steady-state analysis; wavelet analysis
History: received April 2004; revised July 2005; accepted August 2005.