Next: 4. Multivariate Density Estimation
Up: csahtml
Previous: 3.6 Conclusions
-
- 1
-
Alam, F.M., K.R. McNaught, T.J. Ringrose (2003). A comparison of experimental
designs in the development of a neural network simulation metamodel.
Simulation Modelling: Practice and Theory, accepted conditionally.
- 2
-
Angün, E., D. den Hertog, G. Gürkan, J.P.C. Kleijnen (2002). Response
surface methodology revisited. In: Proceedings of the 2002 Winter Simulation Conference, ed. E. Yücesan, C.H. Chen, J.L.
Snowdon, J.M. Charnes, Piscataway, New Jersey: Institute of Electrical and
Electronics Engineers, 377-383.
- 3
-
Antioniadis, A., D.T. Pham (1998). Wavelet regression for random or irregular
design. Computational Statistics and data Analysis 28:353-369.
- 4
-
Bettonvil, B., J.P.C. Kleijnen (1990). Measurement scales and resolution IV
designs. American Journal of Mathematical and Management Sciences 10 (3-4): 309-322.
- 5
-
Clarke, S.M., J.H Griebsch, T.W., Simpson (2003). Analysis of support vector
regression for approximation of complex engineering analyses. Proceedings of DETC '03, ASME 2003 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Chicago.
- 6
-
Cressie, N.A.C (1993). Statistics for spatial data. New York: Wiley.
- 7
-
Donohue, J. M., E.C. Houck, R.H. Myers (1993). Simulation designs and
correlation induction for reducing second-order bias in first-order response
surfaces Operations Research 41 (5):880-902.
- 8
- Efron, B. and R.J. Tibshirani (1993). An introduction to
the bootstrap. New York: Chapman & Hall.
- 9
-
Glasserman, P., P. Heidelberger, and P. Shahabuddin (2000), Variance
reduction techniques for estimating value-at-risk. Management Science, 46, no. 10, pp.
1349-1364.
- 10
-
Horne, G., M. Leonardi, eds (2001). Maneuver warfare science 2001. Quantico, Virginia: Defense Automatic
Printing Service.
- 11
-
Jin, R, W. Chen, and A. Sudjianto (2002). On sequential sampling
for global metamodeling in engineering design. Proceedings ofD ETC
'02, ASME 2002 Design Engineering Technical Conferences and Computers
and Information in Engineering Conference, DETC2002/DAC-34092, September
29-October 2, 2002, Montreal, Canada.
- 12
-
Kleijnen, J.P.C (1998). Experimental design for sensitivity analysis,
optimization, and validation of simulation models. In: Handbook of Simulation, ed. J. Banks,
173-223. New York: Wiley.
- 13
-
Kleijnen, J.P.C (1992). Regression metamodels for simulation with common
random numbers: comparison of validation tests and confidence intervals.
Management Science 38 (8): 1164-1185.
- 14
-
Kleijnen, J.P.C (1987). Statistical tools for simulation practitioners. New York: Marcel Dekker.
- 15
-
Kleijnen, J.P.C (1975). Statistical techniques in simulation, volume II. New York: Marcel Dekker. (Russian translation,
Publishing House ''Statistics'', Moscow, 1978).
- 16
-
Kleijnen, J.P.C. S.M. Sanchez, T.W. Lucas, T.M. Cioppa (2003a). A user's
guide to the brave new world of designing simulation experiments. INFORMS Journal on Computing (accepted conditionally).
- 17
-
Kleijnen, J.P.C., B. Bettonvil, F. Person (2003b). Finding the important
factors in large discrete-event simulation: sequential bifurcation and its
applications. In: Screening, ed. A.M. Dean, S.M. Lewis, New York: Springer-Verlag
(forthcoming; preprint:
http://center.kub.nl/staff/kleijnen/papers.html).
- 18
-
Kleijnen, J.P.C. and R.Y. Rubinstein (2001). Monte Carlo sampling and
variance reduction techniques. Encyclopedia of Operations Research and Management Science, Second edition, edited by S. Gass and C.
Harris, Kluwer Academic Publishers, Boston, 2001, pp. 524-526.
- 19
-
Kleijnen, J.P.C., R.G. Sargent (2000). A methodology for the fitting and
validation of metamodels in simulation. European Journal of Operational Research 120 (1): 14-29.
- 20
-
Kleijnen, J.P.C., W.C.M. Van Beers 2003a. Robustness of Kriging when
interpolating in random simulation with heterogeneous variances: some
experiments. European Journal of Operational Research (in press).
- 21
-
Kleijnen, J.P.C., W.C.M. Van Beers. 2003b. Application-driven sequential
designs for simulation experiments: Kriging metamodeling.
Journal Operational Research Society (in press);
preprint:
http://center.kub.nl/staff/kleijnen/papers.html).
- 22
-
Koehler, J.R., A.B. Owen (1996). Computer experiments. In: Handbook of Statistics, Volume 13, Eds. S. Ghosh,
C.R. Rao, 261-308. Amsterdam: Elsevier.
- 23
-
Law, A.M., W.D. Kelton (2000). Simulation modeling and
analysis. 3rd ed. New York: McGraw-Hill
- 24
-
Lophaven, S.N., H.B. Nielsen, and J. Sondergaard (2002). DACE: a Matlab Kriging toolbox, version 2.0. IMM Technical
University of Denmark, Lyngby.
- 25
-
McKay, M.D., R.J. Beckman, W.J. Conover (1979). A comparison of three methods
for selecting values of input variables in the analysis of output from
a computer code. Technometrics 21 (2): 239-245 (reprinted in 2000: Technometrics 42 (1): 55-61).
- 26
-
Meckesheimer, M., R.R. Barton, F. Limayem, B. Yannou (2001). Metamodeling of
combined discrete/continuous responses. AIAA Journal 39 1950-1959.
- 27
-
Rechtschaffner, R.L (1967). Saturated fractions of 2n and 3n factorial
designs. Technometrics 9 569575.
- 28
-
Sacks, J., W.J. Welch, T.J. Mitchell, H.P. Wynn (1989). Design and analysis
of computer experiments. Statistical Science 4 (4) 409-435.
- 29
-
Santner, T.J., B.J. Williams, and W.I. Notz (2003), The design and
analysis of computer experiments. New York: Springer-Verlag.
- 30
-
Simpson, T.W., T.M. Mauery, J.J. Korte, F. Mistree (2001). Kriging metamodels
for global approximation in simulation-based multidisciplinary design
optimization. AIAA Journal 39 (12) 2233-2241.
- 31
-
Spall, J.C (2003). Introduction to stochastic search and optimization; estimation, simulation, and control. Hoboken, New Jersey, Wiley.
- 32
-
Taguchi, G. 1987. System of experimental designs, Volumes 1 and 2. White Plains, NY: UNIPUB/Krauss International.
- 33
-
Yamada, S., Lin, D. K. J. (2002). Construction of mixed-level supersaturated
design, Metrika (56), 205-214.
- 34
-
Ye, K.Q. (1998). Orthogonal column Latin hypercubes and their application in
computer experiments. Journal Association Statistical Analysis, Theory and Methods, (93) 1430-1439.
- 35
-
Zeigler B.P., K. Praehofer, T.G. Kim (2000). Theory of modeling and simulation. 2nd ed. New York: Academic Press.
Subsections