size_a.three_way: Three-way analysis of variance - mixed classification (A in...

In OPDOE: Optimal Design of Experiments

Description

Returns the optimal number of levels for factor A (and B).

Usage

size_a.three_way_mixed_cxbina.model_3_c(alpha, beta, delta, b, c, n, cases)
size_a.three_way_mixed_cxbina.model_7_c(alpha, beta, delta, b, c, n, cases)
size_ab.three_way_mixed_cxbina.model_7_c(alpha, beta, delta, c, n, cases)

Arguments

alpha	Risk of 1st kind
beta	Risk of 2nd kind
delta	The minimum difference to be detected
b	Number of levels of fixed factor B
c	Number of levels of fixed factor C
n	Number of replications
cases	Specifies whether the "maximin" or "maximin" sizes are to be determined

Details

see chapter 3 in the referenced book

Value

Integer(s) giving the size(s).

Note

Better use size.anova which allows a cleaner notation.

Author(s)

Dieter Rasch, Juergen Pilz, L.R. Verdooren, Albrecht Gebhardt, Minghui Wang

References

Dieter Rasch, Juergen Pilz, L.R. Verdooren, Albrecht Gebhardt: Optimal Experimental Design with R, Chapman and Hall/CRC, 2011

See Also

size.anova

Examples

size_a.three_way_mixed_cxbina.model_3_c(0.05, 0.1, 0.5, 5, 4, 1, "maximin")
size_a.three_way_mixed_cxbina.model_3_c(0.05, 0.1, 0.5, 5, 4, 1, "minimin")
size_a.three_way_mixed_cxbina.model_7_c(0.05, 0.1, 0.5, 5, 4, 1, "maximin")
size_a.three_way_mixed_cxbina.model_7_c(0.05, 0.1, 0.5, 5, 4, 1, "minimin")
size_ab.three_way_mixed_cxbina.model_7_c(0.05,0.1,0.50, 5,2,  "maximin")
size_ab.three_way_mixed_cxbina.model_7_c(0.05,0.1,0.50, 5,2,  "minimin")

OPDOE documentation built on May 1, 2019, 8:45 p.m.