IndexWizard (version 0.2.1.0)

SelInd: Function to calculate selection index

Description

Function to calculate selection index

Usage

SelInd(
  w,
  G,
  r2,
  H = NULL,
  i = NULL,
  h2 = NULL,
  d_G_obs = NULL,
  delta = 1e-04,
  verbose = TRUE
)

Value

A list of class SelInd

Arguments

w

Numeric vector of n economic weights. Traits present in G, but not part of the index need to be coded as 0. If traits of G are missing, they will be added automatically with zero weight. Required.

G

Named n*n genetic variance- covariance matrix. Dimnames of G need to match w to ensure correct sorting. Required.

r2

Named numeric vector of reliabilities with length m. Required.

H

Named m*m variance-covariance matrix of estimated breeding to internally derive the residual variance-covariance matrix. If H contains more traits than r2, it will be subsetted.

i

Selection intensity

h2

named numeric vector of length n containing heritabilities for the traits

d_G_obs

named numeric vector of length n containing the observed composition of the genetic gain scaled in genetic standard deviations. If sum(d_G_obs) != 1, it will be rescaled.

delta

small increment to calculate approximate first derivative

verbose

Shall information be printed?

Details

The framework allows to have less traits in the selection index than in the breeding goal (m < n). Calculation of realized economic weights, however, requires m == n.

Examples

tn <- c("RZM", "RZN", "RZEo")
G <- matrix(
    c(1.0,0.13,0.13,
    0.13,1.0,0.23,
    0.13,0.23,1.0),
    3, 3, dimnames = list(tn,tn)
    ) * 144
w <- c(0.7, 0.3, 0)
names(w) <- tn
r2 <- c(0.743, 0.673)
names(r2) <- tn[1:2]
SelInd(
  w = w,
  G = G,
  r2 = r2
)