rmaxa: Maximum admissible gain

In maxRgain: Maximizing Polyclonal Selection Gains Using Integer Programming

Maximum admissible gain

Description

The maximum admissible genetic gain in one trait that can be achieved without decreasing any of the other traits, as a percentage of the overall mean. This function calculates the maximum admissible gains achieved in the specified traits.

Usage

rmaxa(
  traits,
  ref = NULL,
  clmin = 2,
  clmax,
  constraints = NULL,
  meanvec = NULL,
  criteria = NULL,
  data
)

Arguments

traits	A vector with the names of the columns in the data corresponding to the target traits to be optimized, i.e., those included in the objective function.
ref	Name of the reference column (e.g., genotype ID). Defaults to the first column.
clmin	An integer specifying the minimum group size. If omitted, equal to 2.
clmax	An integer specifying the maximum group size. If omitted, equal to clmin.
constraints	Vector with traits to which constraints apply. If omitted, all except ref are used.
meanvec	A named numeric vector of trait means; if omitted, data are assumed to be already normalized by the mean.
criteria	A named numeric vector indicating the selection criterion for each trait: 1 for traits to be increased, -1 for traits to be decreased. If omitted, all traits are assumed to be selected for increase.
data	A data frame comprising the input data consisting of the Predictors of genetic effects, which serve as the basis for the selection procedure.

Value

A list with the following components:

• gain with the gains of the several traits in each dimension

• ⁠selected_<trait>⁠ with the reference of the clones selected in the group of each dimension in each trait

Note

The order of traits must be consistent across traits, constraints, meanvec, and criteria. Both meanvec and criteria must include values for all traits specified in traits and constraints. If constraints is omitted, all traits in the dataset are considered; in that case, meanvec and criteria must provide values for all of them.

References

Surgy, S., Cadima, J. & Gonçalves, E. Integer programming as a powerful tool for polyclonal selection in ancient grapevine varieties. Theor Appl Genet 138, 122 (2025). \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s00122-025-04885-0")}

Examples

mymeanvec <- c(yd = 3.517, pa = 12.760, ta = 4.495, ph = 3.927, bw = 1.653)
mytraits <- c("yd", "pa")
mycriteria <- c(yd = 1, pa = 1, ta = 1, ph = -1, bw = -1)
maxadm <- rmaxa(
   traits = mytraits,
   clmin = 7,
   clmax = 20,
   meanvec = mymeanvec,
   criteria = mycriteria,
   data = Gouveio
   )
maxadm

maxRgain documentation built on Aug. 18, 2025, 5:28 p.m.