EvaluateCore (version 0.1.1)

vr.evaluate.core: Variable Rate of Coefficient of Variation

Description

Compute the Variable Rate of Coefficient of Variation () hu_methods_2000EvaluateCore to compare quantitative traits of the entire collection (EC) and core set (CS).

Usage

vr.evaluate.core(data, names, quantitative, selected)

Arguments

data

The data as a data frame object. The data frame should possess one row per individual and columns with the individual names and multiple trait/character data.

names

Name of column with the individual names as a character string

quantitative

Name of columns with the quantitative traits as a character vector.

selected

Character vector with the names of individuals selected in core collection and present in the names column.

Value

The value.

Details

The Variable Rate of Coefficient of Variation () is computed as follows.

Where,

is the coefficients of variation for the th trait in the CS,

is the coefficients of variation for the th trait in the EC and is the total number of traits

References

Examples

# NOT RUN {
####################################
# Use data from R package ccChooser
####################################

library(ccChooser)
data("dactylis_CC")
data("dactylis_EC")

ec <- cbind(genotypes = rownames(dactylis_EC), dactylis_EC[, -1])
ec$genotypes <- as.character(ec$genotypes)
rownames(ec) <- NULL
ec[, c("X1", "X6", "X7")] <- lapply(ec[, c("X1", "X6", "X7")],
                                    function(x) cut(x, breaks = 4))
ec[, c("X1", "X6", "X7")] <- lapply(ec[, c("X1", "X6", "X7")],
                                    function(x) factor(as.numeric(x)))
head(ec)

core <- rownames(dactylis_CC)

quant <- c("X2", "X3", "X4", "X5", "X8")
qual <- c("X1", "X6", "X7")

####################################
# EvaluateCore
####################################

vr.evaluate.core(data = ec, names = "genotypes",
                 quantitative = quant, selected = core)


# }