sparse_allocation: Unreplicated designs using the sparse allocation approach

In FielDHub: A Shiny App for Design of Experiments in Life Sciences

Unreplicated designs using the sparse allocation approach

Description

Unreplicated designs using the sparse allocation approach

Usage

sparse_allocation(
  lines,
  nrows,
  ncols,
  l,
  planter = "serpentine",
  plotNumber,
  copies_per_entry,
  checks = NULL,
  exptName = NULL,
  locationNames,
  sparse_list,
  seed,
  data = NULL
)

Arguments

lines	Number of genotypes, experimental lines or treatments.
nrows	Number of rows in the field.
ncols	Number of columns in the field.
l	Number of locations or sites. By default l = 1.
planter	Option for serpentine or cartesian plot arrangement. By default planter = 'serpentine'.
plotNumber	Numeric vector with the starting plot number for each location. By default plotNumber = 101.
copies_per_entry	Number of copies per plant. When design is sparse then copies_per_entry < l
checks	Number of genotypes checks.
exptName	(optional) Name of the experiment.
locationNames	(optional) Names each location.
sparse_list	(optional) A class "Sparse" object generated by do_optim() function.
seed	(optional) Real number that specifies the starting seed to obtain reproducible designs.
data	(optional) Data frame with 2 columns: ENTRY | NAME . ENTRY must be numeric.

Value

A list with four elements.

• designs is a list with each location unreplicated randomization.

• list_locs is a list with each location list of entries.

• allocation is a matrix with the allocation of treatments.

• size_locations is a data frame with one column for each location and one row with the size of the location.

Author(s)

Didier Murillo [aut], Salvador Gezan [aut], Ana Heilman [ctb]

References

Edmondson, R.N. Multi-level Block Designs for Comparative Experiments. JABES 25, 500–522 (2020). https://doi.org/10.1007/s13253-020-00416-0

Examples

sparse <- sparse_allocation(
  lines = 120, 
  l = 4, 
  copies_per_entry = 3, 
  checks = 4, 
  locationNames = c("LOC1", "LOC2", "LOC3", "LOC4", "LOC5"), 
  seed = 1234
)

FielDHub documentation built on Sept. 11, 2024, 5:29 p.m.