Skip to contents

Unreplicated designs using the sparse allocation approach

Source: R/fct_sparse_allocation.R
sparse_allocation.Rd

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,
  year = NULL,
  checksPercent = 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.

year

(optional) Year recorded in the YEAR column of the field book. By default the current year.

checksPercent

(optional) Percentage of checks in each location, one of the options available for the field. By default the last (largest) option.

Value

A list with eight elements.

  • infoDesign is a list with information on the design parameters.

  • layoutRandom is a list with the randomization layout of each location.

  • plotsNumber is a list with the plot number layout of each location.

  • data_entry is a data frame with the data input.

  • fieldBook is a data frame with the field book of all locations.

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

  • allocation is a matrix with the allocation of treatments.

  • size_locations is a named vector with the number of lines allocated to each location.

Reproducibility

The result records effective inputs and the resolved seed in metadata$parameters. Under the same package versions and RNG settings, rebuild a result x with do.call(sparse_allocation, x$metadata$parameters).

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

Author

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

Examples

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