The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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