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Largest eigenvalue of the prediction error variance matrix of the target rows, \(X_0 (X'X + \lambda I)^{-1} X_0'\), with an intercept column added. Smaller is better.

Usage

gopt_score(X, X0, lambda = NULL)

Arguments

X

A numeric matrix of the training set (row: individual; column: marker or PC).

X0

A numeric matrix of the target rows (the test set), with the same columns as X.

lambda

A positive number, the ridge penalty, or NULL (default) for the default of the criterion.

Value

A number.

Details

See criteria for the list of criteria and the package website for one page per criterion.

References

Akdemir, D., & Isidro-Sanchez, J. (2019). Design of training populations for selective phenotyping in genomic prediction. Scientific Reports, 9, 1446. <doi:10.1038/s41598-018-38081-6>

Author

Jen-Hsiang Ou

Examples

data(geno)
gopt_score(geno[1:50, ], geno[51:100, ])
#> [1] 20127415