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

In EvaluateCore: Quality Evaluation of Core Collections

Variable Rate of Coefficient of Variation

Description

Compute the Variable Rate of Coefficient of Variation (\mjseqnVR) \insertCitehu_methods_2000EvaluateCore to compare quantitative traits of the entire collection (EC) and core set (CS). \loadmathjax

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.

Details

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

\mjsdeqn

VR = \left ( \frac1n \sum_i=1^n \fracCV_CS_iCV_EC_i \right ) \times 100

Where, \mjseqnCV_CS_i is the coefficients of variation for the \mjseqnith trait in the CS, \mjseqnCV_EC_i is the coefficients of variation for the \mjseqnith trait in the EC and \mjseqnn is the total number of traits

Value

The \mjseqnVR value.

References

\insertAllCited

Examples

data("cassava_CC")
data("cassava_EC")

ec <- cbind(genotypes = rownames(cassava_EC), cassava_EC)
ec$genotypes <- as.character(ec$genotypes)
rownames(ec) <- NULL

core <- rownames(cassava_CC)

quant <- c("NMSR", "TTRN", "TFWSR", "TTRW", "TFWSS", "TTSW", "TTPW", "AVPW",
           "ARSR", "SRDM")
qual <- c("CUAL", "LNGS", "PTLC", "DSTA", "LFRT", "LBTEF", "CBTR", "NMLB",
          "ANGB", "CUAL9M", "LVC9M", "TNPR9M", "PL9M", "STRP", "STRC",
          "PSTR")

ec[, qual] <- lapply(ec[, qual],
                     function(x) factor(as.factor(x)))

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

EvaluateCore documentation built on July 3, 2022, 5:06 p.m.