block.catlg3 | R Documentation |
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.
block.catlg
block.catlg3
Yates
Yates3
The constants documented here are used for blocking full factorial designs
with function fac.design
; Yates
and block.catlg
are
internal here, as they have long been part of package FrF2-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).
Data frame block.catlg
comes from Sun, Wu and Chen (1997).
Data frame 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
list(1,2,c(1,2),3,c(1,3),c(2,3),c(1,2,3))
.
Yates3
is a constant for 3-level designs,
for which there are coefficients rather than generating factor numbers in the list.
Ulrike Groemping
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^n
and 2^{n-p}
designs. Technometrics 39,
298-307.
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