Sequential experimental designs for simulation metamodeling

Subscribe (Full Service)


	Search: The ACM Digital Library The Guide

	Feedback

Sequential experimental designs for simulation metamodeling

Full text

Pdf (966 KB)

Source

Winter Simulation Conference archive
Proceedings of the 24th conference on Winter simulation table of contents

Arlington, Virginia, United States

Pages: 539 - 547

Year of Publication: 1992

ISBN:0-7803-0798-4

Authors

Joan M. Donohue
Ernest C. Houck
Raymond H. Myers

Sponsors

ASA : American Statistical Association
NIST : National Institue of Standards & Technology
IEEE-CS : Computer Society
IEEE-SMCS : Systems, Man & Cybernetics Society
ACM: Association for Computing Machinery
ORSA : Operations Research Society of America
SIGSIM: ACM Special Interest Group on Simulation and Modeling
TIMS :
IIE : Institute of Industrial Engineers
SCS : Society for Computer Simulation

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 2, Downloads (12 Months): 14, Citation Count: 2

Additional Information:

references cited by index terms collaborative colleagues

Tools and Actions:	Review this Article Save this Article to a Binder Display Formats: BibTeX EndNote ACM Ref

DOI Bookmark:	Use this link to bookmark this Article: http://doi.acm.org/10.1145/167293.167635 What is a DOI?

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Bartlett, M. S. 1937. Properties of sufficiency and statistical tests. Proceedings of the Royal Society A 160:268-282.
	2	Box, G. E. P., and N. R. Draper. 1959. A basis for the selection of a response surface design. Journal of the American Statistical Association 54:622-654.
	3	George E P Box , Norman R Draper, Empirical model-building and response surface, John Wiley & Sons, Inc., New York, NY, 1986
	4	Conover, W. J., M. E. Johnson, M. E., and M. M. Johnson. 1981. A comparative study of tests for homogeneity of variances, with applications to the outer continental shelf bidding data. Technomettics 21:351-361.
	5	Donohue, J. M., E. C. Houck, and R. H. Myers. 1992a. Simulation designs and correlation induction for reducing second-order bias in first-order response surfaces. Technical Report, Department of Statistics, Virginia Tech, Blacksburg, Virginia.
	6	Joan M. Donohue , Ernest C. Houck , Raymond H. Myers, Simulation designs for quadratic response surface models in the presence of model misspecification, Management Science, v.38 n.12, p.1765-1791, Dec. 1992 [doi>10.1287/mnsc.38.12.1765]
	7	Donohue, J. M., E. C. Houck, and R. H. Myers. 1992c. Sequential experimental designs for the estimation of first- and second-order simulation metamodels. Working paper, Department of Management Science, University of South Carolina, Columbia, South Carolina.
	8	James R. Hussey , Raymond H. Myers , Ernest C. Houck, Correlated simulation experiments in first-order response surface design, Operations Research, v.35 n.5, p.744-758, September-October 1987 [doi>10.1287/opre.35.5.744]
	9	Hussey, J. R., R. H. Myers, and E. C. Houck. 1987b. Pseudorandom number assignments in quadratic response surface designs. IEE Transactions 19:395-403.
	10	joshi, S., and J. D. Tew. 1992. Statistical analysis and validation procedures under the common random number correlation-induction strategy. To appear in European Journal of Operational Research.
	11	A. I. Khuri , J. A. Cornell, Response surfaces: designs and analyses, Marcel Dekker, Inc., New York, NY, 1987
	12	Kiefer, J. 1978. Comment" Pseudorandom number assignment in statistically designed simulation and distribution sampling experiments, journal of the American Statiatical A~sociation 73:523-524.
	13	Jack P. C. Kleijnen, Regression metamodels for simulation with common random numbers: comparison of validation tests and confidence intervals, Management Science, v.38 n.8, p.1164-1185, Aug. 1992 [doi>10.1287/mnsc.38.8.1164]
	14	Averill M. Law , W. David Kelton, Simulation Modeling and Analysis, McGraw-Hill Higher Education, 1997
	15	Morrison, D. F. (1990). Multivariate statistical methods. 3d ed. New York: McGraw-Hill.
	16	Myers, R. H. 1976. Response surface methodology. Ann Arbor, Michigan" Edward Brothers.
	17	Myers, R. it., and S. j. Lahoda. 1975. A generalization of the response surface mean square error criterion with a specific application to the slope. Technomelrics 17:481-486.
	18	A. Nozari , S. F. Arnold , C. D. Pegden, Statistical analysis for use with the Schruben and Margolin correlation induction strategy, Operations Research, v.35 n.1, p.127-139, Jan.-Feb. 1987 [doi>10.1051/ro:2001107]
	19	Rao, C. R. 1973. Linear statistical inference and its applications. 2d ed. New York: John Wiley & Sons.
	20	Schruben, L. W., and B. H. Margolin. 1978. Pseudorandom number assignment in statistically designed simulation and distribution sampling experiments. Journal of the American Statistical Association 73:504-520.
	21	Silver, N. C., and W. P. Dunlap. 1987. Averaging correlation coefficients: Should Fisher's Z transformation be used? Journal of Applied Psychology 72:146-148.
	22	Jeffrey D. Tew , James R. Wilson, Validation of simulation analysis methods for the Schruben-Margolin correlation-induction strategy, Operations Research, v.40 n.1, p.87-103, Jan.–Feb. 1992 [doi>10.1287/opre.40.1.87]
	23	Tew, J. D., and J. R. Wilson. 1992b. Estimating simulation metamodels using combined correlationbased variance reduction techniques. To appear in IEE Transactions.

CITED BY 2

	Phillip A Farrington , James J. Swain, Design of simulation experiments with manufacturing applications, Proceedings of the 25th conference on Winter simulation, p.69-75, December 12-15, 1993, Los Angeles, California, United States
	James J. Swain , Phillip A. Farrington, Designing simulation experiments for evaluating manufacturing systems, Proceedings of the 26th conference on Winter simulation, p.69-76, December 11-14, 1994, Orlando, Florida, United States