blocksdesign

Nested and Crossed Block Designs for Factorial, Fractional Factorial and Unstructured Treatment Sets

Constructs D-optimal or near D-optimal nested and crossed block designs for unstructured or general factorial treatment designs. Where a structured treatment design is required, a D-optimal or near D-optimal treatment design is found based on a suitable model matrix design formula. The required block design is then found for the required treatment design based on a defined set of block factors. The block factors are added in sequence and each added block factor is optimized conditional on all previously added block factors. The block design can have repeated nesting down to any required depth of nesting with either a simple set of nested blocks or a crossed blocks design at each level of nesting. If a crossed blocks design has more than a single plot in each crossed blocks intersection, the determinant of a weighted combination of the information matrix for additive crossed blocks effects and the information matrix for multiplicative crossed blocks effects is used as the design criterion. 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.

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Description file content

Package
blocksdesign
Type
Package
Title
Nested and Crossed Block Designs for Factorial, Fractional Factorial and Unstructured Treatment Sets
Version
3.0
Date
2018-07-01
Author
R. N. Edmondson.
Maintainer
Rodney Edmondson
Depends
R (>= 3.1.0)
Description
Constructs D-optimal or near D-optimal nested and crossed block designs for unstructured or general factorial treatment designs. Where a structured treatment design is required, a D-optimal or near D-optimal treatment design is found based on a suitable model matrix design formula. The required block design is then found for the required treatment design based on a defined set of block factors. The block factors are added in sequence and each added block factor is optimized conditional on all previously added block factors. The block design can have repeated nesting down to any required depth of nesting with either a simple set of nested blocks or a crossed blocks design at each level of nesting. If a crossed blocks design has more than a single plot in each crossed blocks intersection, the determinant of a weighted combination of the information matrix for additive crossed blocks effects and the information matrix for multiplicative crossed blocks effects is used as the design criterion. 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.
License
GPL (>= 2)
Imports
lme4, crossdes
LazyData
true
RoxygenNote
6.0.1
Suggests
knitr, rmarkdown
VignetteBuilder
knitr
NeedsCompilation
no
Packaged
2018-07-01 17:32:23 UTC; rne
Repository
CRAN
Date/Publication
2018-07-01 18:00:03 UTC

install.packages('blocksdesign')

3.0

3 months ago

Rodney Edmondson

GPL (>= 2)

Depends on

R (>= 3.1.0)

Imports

lme4, crossdes

Suggests

knitr, rmarkdown

Discussions