ESTIMATING SIMULATION METAMODELS USING COMBINED CORRELATION-BASED VARIANCE REDUCTION TECHNIQUES

REFERENCES

• Ahmed , M. A. , Gross , D. , and Miller , D. R. , “ Control Variate Models for Estimating Transient Performance Measures in Repairable Item Systems ,” Management Science , 38 , 388 – 399 ( 1992 ).
   Web of Science ®Google Scholar
• Arnold , S. F. , The Theory of Linear Models and Multivariate Analysis , John Wiley & Sons , New York ( 1981 ) .
   Google Scholar
• Chung , K. L. , A Course in Probability Theory , Second Edition , Academic Press , New York ( 1974 ) .
   Google Scholar
• Donohue , J. M. , Houck , E. C. , and Myers , R. H. , “ Simulation Designs and Correlation Induction for Reducing Second-Order Bias in First-Order Response Surfaces ,” Operations Research , 41 ( 1993 ).
   Web of Science ®Google Scholar
• Donohue , J. M. , Houck , E. C. , and Myers , R. H. , “ Simulation Designs for Quadratic Response Surface Models in the Presence of Model Misspecification ,” Management Science , 38 , 1765 – 1791 ( 1992 ).
   Web of Science ®Google Scholar
• Hussey , J. R. , Myers , R. H. ,Houck, E. C, “ Correlated Simulation Experiments in First-Order Response Surface Design ,” Operations Research , 35 , 744 – 758 ( 1987a ).
   Web of Science ®Google Scholar
• Hussey , J. R. , Myers , R. H. ,Houck, E. C, “ Pseudorandom Number Assignment in Quadratic Response Surface Designs ,” IIE Transactions , 19 , 395 – 403 ( 1987b ).
   Web of Science ®Google Scholar
• Muirhead , R. J. , Aspects of Multivariate Statistical Theory , John Wiley & Sons , New York ( 1982 ) .
   Google Scholar
• Myers , R. H. , Response Surface Methodology , Edwards Brothers, Inc. , Ann Arbor , Michigan ( 1976 ) .
   Google Scholar
• Nozari , A. , Arnold , S. F. , and Pegden , C.D. , “ Control Variates for Multipopulation Simulation Experiments ,” IIE Transactions , 16 , 159 – 169 ( 1984 ).
   Web of Science ®Google Scholar
• Nozari , A. , Arnold , S. F. , and Pegden , C. D. , “ Statistical Analysis for Use with the Schruben and Margolin Correlation Induction Strategy ,” Operations Research , 35 . 127 – 139 ( 1987 ).
   Web of Science ®Google Scholar
• Porta Nova , A. M. de O. , and Wilson , J. R. , “ Estimation of Multiresponse Simulation Metamodels Using Control Variates ,” Management Science , 35 , 1316 – 1333 ( 1989 ).
   Web of Science ®Google Scholar
• Pritsker , A. A. B. , The GASP TV Simulation Language , John Wiley & Sons , New York ( 1974 ) .
   Google Scholar
• Pritsker , A. A. B. , Introduction to Simulation and SLAM II, Third Edition , John Wiley & Sons , New York ( 1986 ) .
   Google Scholar
• Schruben , L. W. , and Margolin , B. H. , “ Pseudorandom Number Assignment in Statistically Designed Simulation and Distribution Sampling Experiments ,” Journal of the American Statistical Association . 73 , 504 – 525 ( 1978 ).
   Web of Science ®Google Scholar
• Schruben , L. W. , “ Designing Correlation Induction Strategies for Simulation Experiments ,” in N. R. Adam and A. Dogra-maci (eds.) , Current Issues in Computer Simulation , Academic Press , New York ( 1979 ) .
   Google Scholar
• Seber , G. A. F. , Linear Regression Analysis , John Wiley & Sons , New York ( 1977 ) .
   Google Scholar
• Serfling , R. J. , Approximation Theorems of Mathematical Statistics , John Wiley & Sons , New York ( 1980 ) .
   Google Scholar
• Tew , J. D. , “ Metamodel Estimation Under Correlation Methods for Simulation Experiments ,” Ph.D. Dissertation, School of Industrial Engineering , Purdue University , West Lafayette , Indiana ( 1986 ) .
   Google Scholar
• Tew , J. D. , and Wilson , J. R. , “ Estimating Simulation Metamodels Using Integrated Variance Reduction Techniques ,” in 1988 Proceedings of the Statistical Computing Section , 23 – 32 , American Statistical Association , Alexandria , Virginia ( 1988 ) .
   Google Scholar
• Tew , J. D. , and Wilson , J. R. , “ Validation of Simulation Analysis Methods for the Schruben-Margolin Correlation-Induction Strategy ,” Operations Research , 40 , 87 – 103 ( 1992 ).
   Web of Science ®Google Scholar
• Wilson , J. R. , “ Variance Reduction Techniques for Digital Simulation ,” American Journal of Mathematical and Management Sciences , 4 , 277 – 312 ( 1984 ).
   Google Scholar