The block data frames hold Yates matrix column numbers for blocking full factorials with 2-level (up to 256 runs) and 3-level factors (up to 243 runs). The Yates lists translate these column numbers into effects.
1 2 3 4
The constants documented here are used for blocking full factorial designs
internal here, as they have long been part of package
The block data frames hold Yates matrix column numbers for blocking full factorials with 2-level (up to 256 runs) and 3-level factors (up to 243 runs). The Yates lists translate these column numbers into effects (see below).
block.catlg comes from Sun, Wu and Chen (1997).
block.catlg3 comes from Cheng and Wu (2002, up to 81 runs)
and has been derived from Hinkelmann and Kempthorne (2005, Table 10.6)
for 243 runs. The blocking schemes from the papers are optimal; this has
not been proven for the blocking scheme for 243 runs.
Yates is a user-visible constant that is useful in design construction:
Yates is a list of design column generators in Yates order (for 4096 runs), e.g.
Yates[1:8] is identical to
Yates3 is a constant for 3-level designs,
for which there are coefficients rather than generating factor numbers in the list.
Cheng, S.W. and Wu, C.F.J. (2002). Choice of Optimal Blocking Schemes in Two-Level and Three-Level Designs. Technometrics 44, 269-277.
Hinkelmann, K. and Kempthorne, O. (2005). Design and analysis of experiments, Vol.2. Wiley, New York.
Sun, D.X., Wu, C.F.J. and Chen, Y.Y. (1997). Optimal blocking schemes for 2\^p and 2\^(n-p) designs. Technometrics 39, 298-307.
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