109
Views
1
CrossRef citations to date
0
Altmetric
Original Articles

Robust designs for experiments with blocks

, &
Pages 5363-5379 | Received 19 Feb 2014, Accepted 03 Jul 2014, Published online: 11 Jul 2016

References

  • Bickel, P.J., Herzberg, A.M. (1979). Robustness of design against autocorrelation in time I: asymptotic theory, optimality for location and linear regression. Ann. Stat. 7:77–95.
  • Bickel, P.J., Herzberg, A.M., Schilling, M.F. (1981). Robustness of design against autocorrelation in time II: optimality, theoretical and numerical results for the first-order autoregressive process. J. Am. Stat. Assoc. 76:870–877.
  • Box, G.E.P., Draper, N.R. (1959). A basis for the selection of a response surface design. J. Am. Stat. Assoc. 54:622–654.
  • Elliott, L.J., Eccleston, J.A., Martin, R.J. (1999). An algorithm for the design of factorial experiments when the data are correlated. Stat. Comput. 9:195–201.
  • Fang, Z., Wiens, D.P. (2000). Integer-valued, minimax robust designs for estimation and extrapolation in heteroscedastic, approximately linear models. J. Am. Stat. Assoc. 95:807–818.
  • Fedorov, V. (2010). Optimal Experimental Design. New York: Wiley.
  • Herzberg, A.M. (1982). The design of experiments for correlated error structures: layout and robustness. Can. J. Stat. 10:133–138.
  • Horn, R., Johnson, C. (1985). Matrix Analysis. Cambridge: Cambridge University Press.
  • Huber, P.J. (1975). Robustness and designs. In A Survey of Statistical Designs and Linear Models: Proceedings of an International Symposium on Statistical Designs and Linear Models, Colorado State University, Fort Collins, March 19–23, 1973, North Holland, Amsterdam (pp. 287–303).
  • Mann, R.K. (2011). Robust designs for field experiments with blocks. MSc thesis. University of Victoria, Victoria, BC, Canada.
  • Martin, R.J. (1982). Some aspects of experimental design and analysis when errors are correlated. Biometrika 69:597–612.
  • Martin, R.J. (1986). On the design of experiments under spatial correlation. Biometrika 73:247–277 (Correction 75, 396, 1988).
  • Montgomery, D.C. (2012). Design and Analysis of Experiments (8th ed.) New York: Wiley.
  • Ou, B., Zhou, J. (2009). Minimax robust designs for field experiments. Metrika 69:45–54.
  • Pukelsheim, F. (1993). Optimal Design of Experiments. New York: Wiley.
  • Shi, P., Ye, J., Zhou, J. (2007). Discrete minimax designs for regression models with autocorrelated MA errors. J. Stat. Plann. Inference 137:2721–2731.
  • Wiens, D.P. (1992). Minimax designs for approximately linear regression. J. Stat. Plann. Inference 31:353–371.
  • Wiens, D.P., Zhou, J. (1997). Robust designs based on the infinitesimal approach. J. Am. Stat. Assoc. 92:1503–1511.
  • Wiens, D.P., Zhou, J. (1999). Minimax designs for approximately linear models with AR(1) errors. Can. J. Stat. 27:781–794.
  • Wiens, D.P., Zhou, J. (2008). Robust estimators and designs for field experiments. J. Stat. Plann. Inference 138:93–104.
  • Williams, R.M. (1952). Experimental designs for serially correlated observations. Biometrika 39:151–167.
  • Wilmut, M., Zhou, J. (2011). D-optimal minimax design criterion for two-level fractional factorial designs. J. Stat. Plann. Inference 141:576–587.
  • Zhou, J. (2001). Integer-valued, minimax robust designs for approximately linear models with correlated errors. Commun. Stat.: Theory Methods 30:21–39.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.