bdf3.mef: Efficient Block Designs for 3-Level Factorial Experiments in...

In bdf3: Efficient Block Designs for 3-Level Factorial Experiments in Block Size 3

Efficient Block Designs for 3-Level Factorial Experiments in Block Size 3

Description

Constructs efficient block designs for 3-level factorial experiments in block size 3, ensuring estimation of all main effects (with full efficiency) and two-factor interactions.

Usage

bdf3.mef(n_factors, show_efficiency = TRUE)

Arguments

n_factors	An integer specifying the number of factors.
show_efficiency	Logical. If TRUE, efficiency factors are computed and displayed; if FALSE, they are omitted.

Details

This function generates efficient block designs for 3-level factorial experiments in block size 3. The resulting designs allow estimation of all main effects (with full efficiency) and two-factor interactions in minimum number of replications.

Value

A list containing:

blocks	The chosen principal blocks
confounded_effects	The confounded main effects and two-factor interactions
efficiency_factors	Efficiency factors of all main effects and two-factor interactions (if show_efficiency = TRUE)
design	The final block design for the given number of factors

References

Dey, A. and Mukerjee, R. (2012). Efficiency factors for natural contrasts in partially confounded factorial designs. Statistics and Probability Letters, 82(12), 2180–2188. <doi:10.1016/j.spl.2012.06.014>

Dash, S., Parsad, R. and Gupta, V. K. (2013). Row–column designs for 2^n factorial 2-colour microarray experiments for estimation of main effects and two-factor interactions with orthogonal parameterization. Agricultural Research, 2(2), 172-182. <doi:10.1007/s40003-013-0059-5>

See Also

bdf3.mep

Examples

bdf3.mef(2)

bdf3 documentation built on Sept. 14, 2025, 5:09 p.m.