Package: dmm 2.1-10
dmm: Dyadic Mixed Model for Pedigree Data
Dyadic mixed model analysis with multi-trait responses and pedigree-based partitioning of individual variation into a range of environmental and genetic variance components for individual and maternal effects. Method documented in dmmOverview.pdf; dmm is an implementation of dispersion mean model described by Searle et al. (1992) "Variance Components", Wiley, NY.
Authors:
dmm_2.1-10.tar.gz
dmm_2.1-10.zip(r-4.5)dmm_2.1-10.zip(r-4.4)dmm_2.1-10.zip(r-4.3)
dmm_2.1-10.tgz(r-4.4-any)dmm_2.1-10.tgz(r-4.3-any)
dmm_2.1-10.tar.gz(r-4.5-noble)dmm_2.1-10.tar.gz(r-4.4-noble)
dmm_2.1-10.tgz(r-4.4-emscripten)dmm_2.1-10.tgz(r-4.3-emscripten)
dmm.pdf |dmm.html✨
dmm/json (API)
# Install 'dmm' in R: |
install.packages('dmm', repos = c('https://nevillejackson.r-universe.dev', 'https://cloud.r-project.org')) |
- dt8bal.df - A balanced dataset with eight individuals.
- harv101.df - Harvey dataset
- merino.df - Australian Merino sheep research dataset
- quercus.df - Quercus example dataset
- sheep.df - Demonstration sheep dataset
- tstmo1.df - Dfreml example dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 months agofrom:0c60afeaab. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 01 2024 |
R-4.5-win | OK | Nov 01 2024 |
R-4.5-linux | OK | Nov 01 2024 |
R-4.4-win | OK | Nov 01 2024 |
R-4.4-mac | OK | Nov 01 2024 |
R-4.3-win | OK | Nov 01 2024 |
R-4.3-mac | OK | Nov 01 2024 |
Exports:chartodeccondense.dmmarraycondense.dmmblockarraycsummarydmmgprintgresponsegsummarymake.countarraymake.ctablemake.dmmobjmdfpedcheckpedrenumunfactorwarcolak.convert