CRAN/E | blocksdesign

blocksdesign

Nested and Crossed Block Designs for Factorial and Unstructured Treatment Sets

Installation

About

Constructs treatment and block designs for linear treatment models with crossed or nested block factors. The treatment design can be any feasible linear model and the block design can be any feasible combination of crossed or nested block factors. The block design is a sum of one or more block factors and the block design is optimized sequentially with the levels of each successive block factor optimized conditional on all previously optimized block factors. D-optimality is used throughout except for square or rectangular lattice block designs which are constructed algebraically using mutually orthogonal Latin squares. Crossed block designs with interaction effects are optimized using a weighting scheme which 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. Edmondson, R.N. Multi-level Block Designs for Comparative Experiments. JABES 25, 500–522 (2020) doi:10.1007/s13253-020-00416-0.

Key Metrics

Version 4.9
R ≥ 3.1
Published 2021-04-07 1112 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks blocksdesign results

Downloads

Yesterday 27 0%
Last 7 days 252 -12%
Last 30 days 1.173 -9%
Last 90 days 3.858 +26%
Last 365 days 12.822 +24%

Maintainer

Maintainer

Rodney Edmondson

rodney.edmondson@gmail.com

Authors

R. N. Edmondson.

Material

Reference manual
Package source

In Views

CausalInference
ExperimentalDesign

Vignettes

R package:'blocksdesign' for Agricultural Experiments

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

blocksdesign archive

Depends

R ≥ 3.1

Imports

plyr
PolynomF

Suggests

R.rsp

Reverse Imports

FielDHub