This package creates various kinds of designs for (industrial) experiments. It uses, and sometimes enhances, design generation routines from other packages. So far, response surface designs from package rsm, designs for computer experiments (latin hypercube samples etc.) from packages lhs and DiceDesign and D-optimal designs from package AlgDesign have been implemented.
Currently, the package provides classical response surface designs from package
rsm: Box-Behnken designs by Box and Behnken (function
and central composite designs by Box and Wilson (
ccd.design) are implemented.
For the latter, there is also a function for augmenting 2-level fractional factorials
into central composite designs (
Furthermore, latin hypercube samples and other designs for computer experiments from packages lhs and DiceDesign are provided.
Furthermore, D-optimal designs have been implemented, using package AlgDesign. This implementation is currently in beta shape.
All designs created by this package are class
which are data frames with attributes.
Apart from providing designs, the package also provides functions for comparing
the quality of several designs with quantitative variables (function
This package is still under (slow) development. Reports about bugs and inconveniences are welcome.
Box, G.E.P. and Behnken, D.W. (1960). Some new three-level designs for the study of quantitative variables. Technometrics 2, 455-475.
Box, G.E.P., Hunter, J.S. and Hunter, W.G. (2005, 2nd ed.). Statistics for Experimenters. Wiley, New York.
Box, G.E.P. and Wilson, K.B. (1951). On the Experimental Attainment of Optimum Conditions. J. Royal Statistical Society, B13, 1-45.
NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/pri/section3/pri3361.htm, accessed August 20th, 2009.
Myers, R.H., Montgomery, D.C. and Anderson-Cook, C.M. (2009). Response Surface Methodology. Process and Product Optimization Using Designed Experiments. Wiley, New York.
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