Multivariate standardized time series for steady-state simulation output analysis

Operations Research

Volumn 49, Issue 3, 2001, Pages 413-422

  Muñoz, David F ^b   Glynn, Peter W ^b  

^a INSTITUTO TECNOLÓGICO AUTÓNOMO DE MÉXICO   (Mexico)

^b NONE

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; ASYMPTOTIC STABILITY; COMPUTER SIMULATION; CONFORMAL MAPPING; MULTIVARIABLE SYSTEMS; PARAMETER ESTIMATION; RANDOM PROCESSES; STANDARDIZATION; THEOREM PROVING; TIME SERIES ANALYSIS;

FUNCTIONAL CENTRAL LIMIT THEOREM; MULTIVARIATE STANDARDIZED TIME SERIES; SCHRUBEN STANDARDIZED SUM PROCESS; STEADY STATE ESTIMATION; STEADY STATE OUTPUT ANALYSIS;

SYSTEMS ANALYSIS;

EID: 0035328442     PISSN: 0030364X     EISSN: None     Source Type: Journal    
DOI: 10.1287/opre.49.3.413.11209     Document Type: Article

References (24)

1. Multivariate inference in stationary simulation using batch means
2. An introduction to the regenerate method for simulation analysis
3. Mean-square consistency of the variance estimator in steady-state simulation output analysis
4. Establishing the positive definiteness of the sample covariance matrix
5. Simulation output analysis using standardized time series
6. Asymptotic properties of some confidence interval estimators for simulation output
7. Large and small sample comparisons of various variance estimators
8. Properties of standardized time series weighted area variance estimators
9. The regenerative method for simulation analysis
10. Statistical analysis of simulation output data
11. Batch size effects in the analysis of simulation output
12. Control of initialization bias in multivariate simulation response
13. Detecting initialization bias in simulation output
14. Confidence interval estimation using standardized time series