mean_performance: Mean performance of phenotypic data

In selection.index: Analysis of Selection Index in Plant Breeding

Mean performance of phenotypic data

Description

Mean performance of phenotypic data

Usage

mean_performance(
  data,
  genotypes,
  replications,
  columns = NULL,
  main_plots = NULL,
  design_type = c("RCBD", "LSD", "SPD"),
  method = c("REML", "Yates", "Healy", "Regression", "Mean", "Bartlett")
)

Arguments

data	data for analysis
genotypes	genotypes vector (sub-plot treatments in SPD)
replications	replication vector
columns	vector containing columns (required for Latin Square Design only)
main_plots	vector containing main plot treatments (required for Split Plot Design only)
design_type	experimental design type: "RCBD" (default), "LSD" (Latin Square), or "SPD" (Split Plot)
method	Method for missing value imputation: "REML" (default), "Yates", "Healy", "Regression", "Mean", or "Bartlett"

Value

Dataframe of mean performance analysis

Examples

mean_performance(data = seldata[, 3:9], genotypes = seldata[, 2], replications = seldata[, 1])

selection.index documentation built on March 9, 2026, 1:06 a.m.