Autoregressive-output-analysis methods revisited
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 st...
Ausführliche Beschreibung
Gespeichert in:
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
1994 |
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| Umfang: |
28 |
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| Reproduktion: |
Springer Online Journal Archives 1860-2002 |
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| Übergeordnetes Werk: |
in: Annals of operations research - 1984, 53(1994) vom: Jan., Seite 391-418 |
| Übergeordnetes Werk: |
volume:53 ; year:1994 ; month:01 ; pages:391-418 ; extent:28 |
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NLEJ196412986 |
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| 520 | |a 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. | ||
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| 700 | 1 | |a Nelson, Barry L. |4 oth | |
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(DE-627)NLEJ196412986 DE-627 ger DE-627 rakwb eng Autoregressive-output-analysis methods revisited 1994 28 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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. Springer Online Journal Archives 1860-2002 Yuan, Mingjian oth Nelson, Barry L. oth in Annals of operations research 1984 53(1994) vom: Jan., Seite 391-418 (DE-627)NLEJ188988866 (DE-600)2021913-1 1572-9338 nnns volume:53 year:1994 month:01 pages:391-418 extent:28 http://dx.doi.org/10.1007/BF02136836 GBV_USEFLAG_U ZDB-1-SOJ GBV_NL_ARTICLE AR 53 1994 1 391-418 28 |
| spelling |
(DE-627)NLEJ196412986 DE-627 ger DE-627 rakwb eng Autoregressive-output-analysis methods revisited 1994 28 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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. Springer Online Journal Archives 1860-2002 Yuan, Mingjian oth Nelson, Barry L. oth in Annals of operations research 1984 53(1994) vom: Jan., Seite 391-418 (DE-627)NLEJ188988866 (DE-600)2021913-1 1572-9338 nnns volume:53 year:1994 month:01 pages:391-418 extent:28 http://dx.doi.org/10.1007/BF02136836 GBV_USEFLAG_U ZDB-1-SOJ GBV_NL_ARTICLE AR 53 1994 1 391-418 28 |
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(DE-627)NLEJ196412986 DE-627 ger DE-627 rakwb eng Autoregressive-output-analysis methods revisited 1994 28 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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. Springer Online Journal Archives 1860-2002 Yuan, Mingjian oth Nelson, Barry L. oth in Annals of operations research 1984 53(1994) vom: Jan., Seite 391-418 (DE-627)NLEJ188988866 (DE-600)2021913-1 1572-9338 nnns volume:53 year:1994 month:01 pages:391-418 extent:28 http://dx.doi.org/10.1007/BF02136836 GBV_USEFLAG_U ZDB-1-SOJ GBV_NL_ARTICLE AR 53 1994 1 391-418 28 |
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(DE-627)NLEJ196412986 DE-627 ger DE-627 rakwb eng Autoregressive-output-analysis methods revisited 1994 28 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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. Springer Online Journal Archives 1860-2002 Yuan, Mingjian oth Nelson, Barry L. oth in Annals of operations research 1984 53(1994) vom: Jan., Seite 391-418 (DE-627)NLEJ188988866 (DE-600)2021913-1 1572-9338 nnns volume:53 year:1994 month:01 pages:391-418 extent:28 http://dx.doi.org/10.1007/BF02136836 GBV_USEFLAG_U ZDB-1-SOJ GBV_NL_ARTICLE AR 53 1994 1 391-418 28 |
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(DE-627)NLEJ196412986 DE-627 ger DE-627 rakwb eng Autoregressive-output-analysis methods revisited 1994 28 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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. Springer Online Journal Archives 1860-2002 Yuan, Mingjian oth Nelson, Barry L. oth in Annals of operations research 1984 53(1994) vom: Jan., Seite 391-418 (DE-627)NLEJ188988866 (DE-600)2021913-1 1572-9338 nnns volume:53 year:1994 month:01 pages:391-418 extent:28 http://dx.doi.org/10.1007/BF02136836 GBV_USEFLAG_U ZDB-1-SOJ GBV_NL_ARTICLE AR 53 1994 1 391-418 28 |
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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. |
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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. |
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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. |
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