References
- Box, G.E.P., Hunter, W.G., Hunter, J.S. (1978). Statistics for Experiments. New York: John Wiley and Sons.
- Chatterjee, K., Li, Z.H., Qin, H. (2012). Some new lower bounds to centered and wrap-round L2-discrepancies. Stat. Probab. Lett. 82:1367–1373.
- Fang, K.T., Lin, D.K.J., Qin, H. (2003). A note on optimal foldover design. Stat. Probab. Lett. 62:245–250.
- Fang, K.T., Mukerjee, R. (2000). Connection between uniformity and aberration in regular fractions of two-level factorials. Biometrika 87:173–198.
- Hickernell, F.J. (1998a). A generalized discrepancy and quadrature error Bound. Math. Comput. 67:299–322.
- Hickernell, F.J. (1998b). Lattice rules: How well do they measure up? In: Random and Quasi-Random Point Sets, eds. P. Hellekalek, and G. Larcher, Lecture Notes in Statistics, Vol. 138:109–166. New York: Springer
- Lei, Y.J., Qin, H., Zou, N. (2010). Some lower bounds of centered L2-discrepancy on foldover designs. Acta. Math. Sinica 30A(6):1555–1561.
- Li, H., Mee, R.W. (2002). Better foldover fractions for resolution III 2k − p designs. Technometrics 44:278–283.
- Li, F., Jacroux, M. (2007). Optimal foldover plans for blocked 2m − k fractional factorial designs. J. Stat. Plann. Inference 137:2439–2452.
- Li, P.F., Liu, M.Q., Zhang, R.C. (2005). Choice of optimal initial designs in sequential experiments. Metrika 61(2):127–135.
- Li, W., Lin, D.K.J. (2003). Optimal foldover plans for two-Level fractional factorial designs. Technometrics 45:142–149.
- Li, W., Lin, D.K.J., Ye, K.Q. (2003). Optimal foldover plans for non-regular orthogonal designs. Technometrics 45:347–351.
- Ma, C.X., Fang, K.T. (2001). A note on generalized aberration factorial designs. Metrika 53:85–93.
- Montgomery, D.C., Runger, G.C. (1996). Foldover of 2k − p resolution IV experimental designs. J. Q. Technol. 28:446–450.
- Ou, Z.J., Chatterjee, K., Qin, H. (2011). Lower bounds of various discrepancies on combined designs. Metrika 74:109–119.
- Wang, B., Robert, G.M., John, F.B. (2010). A note on the selection of optimal foldover plans for 16- and 32-run fractional factorial designs. J. Stat. Plann. Inference 140:1497–1500.