blocksdesign: Nested and Crossed Block Designs for Factorial and Unstructured Treatment Sets

Constructs D-optimal or near D-optimal treatment and block designs for linear treatment models with crossed or nested block factors. The treatment design can be any arbitrary linear model defined by a treatment model formula and the block design can be any feasible combination of crossed or nested block factors. The block design factors are optimized sequentially and the levels of each successive block factor are optimized within the levels of each preceding block factor. Crossed block designs with non-singular interaction effects are optimized using a weighting scheme that allows for differential weighting of first and second-order block effects. Outputs include a table showing the allocation of treatments to blocks and tables showing the achieved D-efficiency factors for each block and treatment design.

Version: 4.4
Depends: R (≥ 3.1.0)
Imports: lme4, plyr, PolynomF
Suggests: R.rsp
Published: 2020-08-28
Author: R. N. Edmondson.
Maintainer: Rodney Edmondson <rodney.edmondson at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: ExperimentalDesign
CRAN checks: blocksdesign results


Reference manual: blocksdesign.pdf
Vignettes: R package:'blocksdesign' for Agricultural Experiments
Package source: blocksdesign_4.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: blocksdesign_4.4.tgz, r-oldrel: blocksdesign_4.4.tgz
Old sources: blocksdesign archive

Reverse dependencies:

Reverse imports: SpatialFloor


Please use the canonical form to link to this page.