Optimal and orthogonal Latin hypercube designs for computer experiments
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[1] E. Williams. Experimental Designs Balanced for the Estimation of Residual Effects of Treatments , 1949 .
[2] R. Iman,et al. A distribution-free approach to inducing rank correlation among input variables , 1982 .
[3] M. Stein. Large sample properties of simulations using latin hypercube sampling , 1987 .
[4] Jerome Sacks,et al. Designs for Computer Experiments , 1989 .
[5] M. E. Johnson,et al. Minimax and maximin distance designs , 1990 .
[6] T. J. Mitchell,et al. Bayesian Prediction of Deterministic Functions, with Applications to the Design and Analysis of Computer Experiments , 1991 .
[7] A. Owen. A Central Limit Theorem for Latin Hypercube Sampling , 1992 .
[8] Henry P. Wynn,et al. Screening, predicting, and computer experiments , 1992 .
[9] T. J. Mitchell,et al. Bayesian design and analysis of computer experiments: Use of derivatives in surface prediction , 1993 .
[10] R. Edmondson. Systematic row-and-column designs balanced for low order polynomial interactions between rows and columns , 1993 .
[11] A. Owen. Controlling correlations in latin hypercube samples , 1994 .
[12] M. Buckley. Fast computation of a discretized thin-plate smoothing spline for image data , 1994 .
[13] T. J. Mitchell,et al. Exploratory designs for computational experiments , 1995 .
[14] Jack P. C. Kleijnen,et al. Sensitivity analysis and related analyses: A review of some statistical techniques , 1997 .
[15] H. Wynn,et al. Lattice-based D-optimum design for Fourier regression , 1997 .
[16] A frequency domain comparison of estimation methods for gaussian fields , 1998 .
[17] M. D. McKay,et al. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code , 2000 .
[18] Thomas J. Santner,et al. Design and analysis of computer experiments , 1998 .