selection.index (version 2.0.0)

gen_varcov: Genotypic Variance-Covariance Analysis

Description

Genotypic Variance-Covariance Analysis

Usage

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

Value

A Genotypic Variance-Covariance Matrix

Arguments

data

traits to be analyzed

genotypes

vector containing genotypes/treatments (sub-plot treatments in SPD)

replication

vector containing replication/blocks (RCBD) or rows (LSD)

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"

Examples

# RCBD example
gen_varcov(data = seldata[, 3:9], genotypes = seldata$treat, replication = seldata$rep)

# Latin Square Design example (requires columns parameter)
# gen_varcov(data=lsd_data[,3:7], genotypes=lsd_data$treat,
#           replication=lsd_data$row, columns=lsd_data$col, design_type="LSD")

# Split Plot Design example (requires main_plots parameter)
# gen_varcov(data=spd_data[,3:7], genotypes=spd_data$subplot,
#           replication=spd_data$block, main_plots=spd_data$mainplot, design_type="SPD")