FielDHub (version 1.4.2)

full_factorial: Generates a Full Factorial Design

Description

It randomly generates a full factorial design across locations.

Usage

full_factorial(
  setfactors = NULL,
  reps = NULL,
  l = 1,
  type = 2,
  plotNumber = 101,
  continuous = FALSE,
  planter = "serpentine",
  seed = NULL,
  locationNames = NULL,
  factorLabels = TRUE,
  data = NULL
)

Value

A list with two elements.

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

• fieldBook is a data frame with the full factorial field book.

Arguments

setfactors

Numeric vector with levels of each factor.

reps

Number of replicates (full blocks).

l

Number of locations. By default l = 1.

type

Option for CRD or RCBD designs. Values are type = 1 (CRD) or type = 2 (RCBD). By default type = 2.

plotNumber

Numeric vector with the starting plot number for each location. By default plotNumber = 101.

continuous

Logical for plot number continuous or not. By default continuous = FALSE.

planter

Option for serpentine or cartesian plot arrangement. By default planter = 'serpentine'.

seed

(optional) Real number that specifies the starting seed to obtain reproducible designs.

locationNames

(optional) Names for each location.

factorLabels

(optional) If TRUE retain the levels labels from the original data set otherwise, numeric labels will be assigned. Default is factorLabels =TRUE.

data

(optional) Data frame with the labels of factors.

Author

Didier Murillo [aut], Salvador Gezan [aut], Ana Heilman [ctb], Thomas Walk [ctb], Johan Aparicio [ctb], Richard Horsley [ctb]

References

Federer, W. T. (1955). Experimental Design. Theory and Application. New York, USA. The Macmillan Company.

Examples

# Example 1: Generates a full factorial with 3 factors each with 2 levels.
# This in an RCBD arrangement with 3 reps.
fullFact1 <- full_factorial(setfactors = c(2,2,2), reps = 3, l = 1, type = 2,
                            plotNumber = 101,
                            continuous = TRUE,
                            planter = "serpentine",
                            seed = 325,
                            locationNames = "FARGO")
fullFact1$infoDesign
head(fullFact1$fieldBook,10)

# Example 2: Generates a full factorial with 3 factors and each with levels: 2,3,
# and 2, respectively. In this case, we show how to use the option data
FACTORS <- rep(c("A", "B", "C"), c(2,3,2))
LEVELS <- c("a0", "a1", "b0", "b1", "b2", "c0", "c1")
data_factorial <- data.frame(list(FACTOR = FACTORS, LEVEL = LEVELS))
print(data_factorial)
# This in an RCBD arrangement with 5 reps in 3 locations.
fullFact2 <- full_factorial(setfactors = NULL, reps = 5, l = 3, type = 2,
                            plotNumber = c(101,1001,2001),
                            continuous = FALSE,
                            planter = "serpentine",
                            seed = 326,
                            locationNames = c("Loc1","Loc2","Loc3"),
                            data = data_factorial)
fullFact2$infoDesign
head(fullFact2$fieldBook,10)