Multivariate mixed model solver for multiple random effects allowing the specification of variance covariance structures. ML/REML estimates are obtained using the Average Information (AI), Expectation-Maximization (EM), Newton-Raphson (NR), or Efficient Mixed Model Association (EMMA) algorithms. Designed for genomic prediction and genome wide association studies (GWAS) to include additive, dominance and epistatic relationship structures or other covariance structures in R, but also functional as a regular mixed model program. Multivariate models (multiple responses) can be fitted currently with NR, AI and EMMA algorithms allowing multiple random effects as well. Covariance structures for the residual component is currently supported only for balanced univariate Newton Raphson models.
| Version: | 2.5 |
| Depends: | R (≥ 2.10), Matrix (≥ 1.1.1), methods, stats, MASS, parallel |
| Suggests: | knitr |
| Published: | 2017-01-03 |
| Author: | Giovanny Covarrubias-Pazaran |
| Maintainer: | Giovanny Covarrubias-Pazaran <cova_ruber at live.com.mx> |
| License: | GPL-3 |
| URL: | http://www.wisc.edu |
| NeedsCompilation: | no |
| Citation: | sommer citation info |
| Materials: | ChangeLog |
| CRAN checks: | sommer results |
| Reference manual: | sommer.pdf |
| Vignettes: |
Genetic analysis using the sommer package |
| Package source: | sommer_2.5.tar.gz |
| Windows binaries: | r-devel: sommer_2.5.zip, r-release: sommer_2.5.zip, r-oldrel: sommer_2.5.zip |
| OS X Mavericks binaries: | r-release: sommer_2.5.tgz, r-oldrel: sommer_2.5.tgz |
| Old sources: | sommer archive |
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