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Estimating Variance Components in a Class of Mixed Models by Restricted Maximum Likelihood
Open accessAbstract
An efficient algorithm is described for computing restricted maximum likelihood estimates of variance components in a class of models.The class of models is characterized by effects to be absorbed, which are nested within herds, other fixed effects, random sire effects, one other group of random effects nested within herds, and a random residual.The model can be generalized to account for relationships among sires.Matrix inversion is not used.A realistic example is presented.
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Metadata
- Authors
- Smith, S. P., & Graser, H.-U.
- Affiliations
- Animal Genetics and Breeding Unit (AU)
- ORCID
- Smith, S.P.
- Venue
- Journal of Dairy Science
- Publisher
- American Dairy Science Association
- Published
- 1986-04
- Volume
- 69
- Issue
- 4
- Pages
- 1156-1165
- ISSN
- 0022-0302 (ISSN-L)
- OpenAlex
- W2166152266
- Semantic Scholar
- 1a2fc193a2369f413cc62858a2d64c762c8a7362
- Cited by
- 247
- References
- 12
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 1 · 2022: 2 · 2021: 2 · 2020: 5 · 2019: 3 · 2018: 1 · 2017: 1 · 2016: 5 · 2015: 2 · 2014: 2 · 2013: 4 · 2012: 2
- FWCI
- 4.82
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Dairy Science (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
- Keywords
- variance components, restricted maximum likelihood, mixed models, herds, nested random effects, fixed effects, dairy cattle, genetic evaluation, matrix inversion avoidance
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