Abstract
We revisit and update the autoregressive-output-analysis method for constructing a confidence interval for the steady-state mean of a simulated process by using Rissanen's predictive least-squares criterion to estimate the autoregressive order of the process. This order estimator is strongly consistent when the output is autoregressive. The order estimator is combined with the standard autoregressive-output-analysis method to form a confidence-interval procedure. Alternatives for estimating the degrees of freedom for the procedure are investigated. The main result is an asymptotically valid confidence-interval procedure that, empirically, has good small-sample properties.
Original language | English (US) |
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Pages (from-to) | 391-418 |
Number of pages | 28 |
Journal | Annals of Operations Research |
Volume | 53 |
Issue number | 1 |
DOIs | |
State | Published - Dec 1994 |
Keywords
- Autoregressive process
- confidence interval
- output analysis
- simulation
- statistics
- time series
ASJC Scopus subject areas
- General Decision Sciences
- Management Science and Operations Research