Package: blocksdesign
Type: Package
Title: Nested and Crossed Block Designs for Factorial, Fractional
Factorial and Unstructured Treatment Sets
Version: 2.8
Date: 2018-04-18
Author: R. N. Edmondson.
Maintainer: Rodney Edmondson <rodney.edmondson@gmail.com>
Depends: R (>= 3.1.0)
Description: The 'blocksdesign' package constructs nested block and
D-optimal factorial designs for any unstructured or factorial
treatment model of any size. The nested block designs can have repeated
nesting down to any required depth of nesting with either a simple set
of nested blocks or a crossed row-and-column blocks design at each level
of nesting. The block design at each level of nesting is optimized for
D-efficiency within the blocks of each preceding set of
blocks. Outputs include a table showing the allocation of
treatments to blocks, a plan layout showing the allocation of treatments
within blocks (unstructured treatment designs only) the achieved
D-efficiency factors for the block and treatment design
(factorial treatment designs only) and, where feasible,
an A-efficiency factor and A-efficiency upper bound for the block design
(unstructured treatment designs only).
License: GPL (>= 2)
Imports: crossdes
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-04-18 20:52:08 UTC; rne
Repository: CRAN
Date/Publication: 2018-04-18 23:17:06 UTC

Package: blocksdesign
Type: Package
Title: Nested and Crossed Block Designs for Factorial, Fractional
Factorial and Unstructured Treatment Sets
Version: 2.9
Date: 2018-06-11"
Author: R. N. Edmondson.
Maintainer: Rodney Edmondson <rodney.edmondson@gmail.com>
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: 2018-06-12 09:40:25 UTC; rne
Repository: CRAN
Date/Publication: 2018-06-12 13:33:48 UTC