Efficient strategies for leave-one-out cross validation for genomic best linear unbiased prediction
Abstract Background A random multiple-regression model that simultaneously fit all allele substitution effects for additive markers or haplotypes as uncorrelated random effects was proposed for Best Linear Unbiased Prediction, using whole-genome data. Leave-one-out cross validation can be used to qu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2017-05-01
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| Series: | Journal of Animal Science and Biotechnology |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s40104-017-0164-6 |