A combinatorial central limit theorem for randomized orthogonal array sampling designs

Annals of Statistics

Volumn 24, Issue 3, 1996, Pages 1209-1224

  Loh, Wei Liem ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Combinatorial central limit theorem; Computer experiment; Convergence rate; Orthogonal array; Sampling design; Stein's method

Indexed keywords

EID: 0030516416     PISSN: 00905364     EISSN: None     Source Type: Journal    
DOI: 10.1214/aos/1032526964     Document Type: Article

References (9)

1. p bound for the remainder in a combinatorial central limit theorem. Ann. Probab. 6 231-249.
2. MCKAY, M. D., CONOVER, W. J. and BECKMAN, R. J. (1979). A comparison of three methods for selecting values of output variables in the analysis of output from a computer code. Technometrics 21 239-245.
3. OWEN, A. B. (1992). Orthogonal arrays for computer experiments, integration and visualization. Statist. Sinica 2 439-452.
4. OWEN, A. B. (1994) Lattice sampling revisited: Monte Carlo variance of means over randomized orthogonal arrays. Ann. Statist. 22 930-945.
5. RAGHAVARAO, D. (1971). Constructions and Combinatorial Problems in Design of Experiments. Wiley, New York.
6. STEIN, C. M. (1972). A bound for the error in the normal approximation to the distribution of a sum of dependent random variables. Proc. Sixth Berkeley Symp. Math. Statist. Probab. 2 583-602. Univ. California Press, Berkeley.
7. STEIN, C. M. (1986). Approximate Computation of Expectations. IMS, Hayward, CA.
8. STEIN, M. L. (1987). Large sample properties of simulations using Latin hypercube sampling. Technometrics 29 143-151.
9. TANG, B. (1993). Orthogonal array-based Latin hypercubes. J. Amer. Statist. Assoc. 88 1392-1397.