Probability of outperforming a check

Measures the precision of estimated values, and the potential response to selection on those estimated values compared to a check

reliability(x, ...)

# Default S3 method
reliability(x, y = NULL, ...)

# S3 method for class 'PlackettLuce'
reliability(x, ref, ...)

# S3 method for class 'pltree'
reliability(x, ref, ...)

Arguments

x

a numeric vector, or an object of class PlackettLuce or pltree

...

additional arguments passed to methods

y

numeric, the reference value

ref

a character or integer for indexing the element containing reference values in x

Value

the reliability based on the worth parameters

References

Eskridge and Mumm (1992). Theoret. Appl. Genetics 84, 494–500 doi:10.1007/BF00229512 .

Author

Kauê de Sousa, David Brown, Jacob van Etten

Examples

# Case 1. vector example

x = c(9.5, 12, 12.3, 17)

y = 11.2

reliability(x, y)

# Case 2. PlackettLuce model

library("PlackettLuce") 

R = matrix(c(1, 2, 4, 3,
              4, 1, 2, 3,
              2, 3, 1, 4,
              4, 2, 3, 1,
              2, 1, 4, 3,
              1, 4, 3, 2), nrow = 6, byrow = TRUE)
colnames(R) = c("apple", "banana", "orange", "pear")

mod = PlackettLuce(R)

reliability(mod, ref = "orange")

# \donttest{
# Case 3. PlackettLuce tree

data("beans", package = "PlackettLuce")

G = rank_tricot(data = beans,
                 items = c(1:3),
                 input = c(4:5),
                 group = TRUE,
                 additional.rank = beans[c(6:8)])

pld = cbind(G, beans[,c("maxTN", "season", "lon")])

tree = pltree(G ~ maxTN + season + lon, data = pld)

reliability(tree, ref = "Local")

# }