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dmm  

Dyadic Mixed Model for Pedigree Data
View on CRAN: Click here


Download and install dmm package within the R console
Install from CRAN:
install.packages("dmm")

Install from Github:
library("remotes")
install_github("cran/dmm")

Install by package version:
library("remotes")
install_version("dmm", "3.2-2")



Attach the package and use:
library("dmm")
Maintained by
Neville Jackson
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-03-14
Latest Update: 2025-07-08
Description:
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.
How to cite:
Neville Jackson (2015). dmm: Dyadic Mixed Model for Pedigree Data. R package version 3.2-2, https://cran.r-project.org/web/packages/dmm. Accessed 07 Mar. 2026.
Previous versions and publish date:
1.5-1 (2015-03-14 14:25), 1.6-1 (2015-05-09 23:12), 1.6-2 (2015-06-27 13:14), 1.6-3 (2015-08-18 15:37), 1.7-1 (2016-04-12 08:12), 2.1-2 (2017-09-27 13:21), 2.1-3 (2018-01-19 11:31), 2.1-4 (2018-06-16 11:36), 2.1-5 (2018-07-16 10:00), 2.1-6 (2020-06-03 10:30), 2.1-7 (2021-04-17 12:20), 2.1-8 (2023-07-17 02:40), 2.1-9 (2023-11-30 00:30), 2.1-10 (2024-06-03 08:30), 3.1-1 (2025-02-25 11:50), 3.2-1 (2025-07-08 12:40)
Other packages that cited dmm R package
View dmm citation profile
Other R packages that dmm depends, imports, suggests or enhances
Complete documentation for dmm
Functions, R codes and Examples using the dmm R package
Some associated functions: chartodec . condense.dmmarray . condense.dmmblockarray . csummary.dmm . dmm-internal . dmm-package . dmm . dt8bal.df . gprint.dmm . gprint . gresponse.dmm . gsummary.dmm . harv101.df . make.countarray . make.ctable . make.dmmobj . mdf . merino.df . pedcheck . pedrenum . plot.dmm . print.csummary.dmm . print.dmm . print.gresponse.dmm . print.gsummary.dmm . print.summary.dmm . quercus.df . sheep.df . summary.dmm . summary.gresponse.dmm . tstmo1.df . unfactor . warcolak.convert . 
Some associated R codes: am.arel.R . am.mcrel.R . am.pyrel.R . am.zandrel.R . chartodec.R . combpaste.R . comtopar.R . comtopar.specific.R . condense.dmmarray.R . condense.dmmblockarray.R . countnotna.R . covcit.R . covlyz.R . covt.R . covtopar.R . crossclasscovtopar.R . crosseffectcovtopar.R . csummary.R . csummary.dmm.R . csummary_specific.R . dae.nonspecific.I.R . dae.nonspecific.R . dae.nonspecific.S.R . dae.specific.I.R . dae.specific.R . dae.specific.S.R . dmesolve.R . dmm-internal.R . dmm.R . dmm.default.R . dmm_array.R . dmm_blockarray.R . duplicated_first.R . dyad.am.expect.R . expect.v.R . fixpaste.R . genericvarvcnames.R . genericvcnames.R . gls.b.gmat.R . gls.iter.b.R . gprint.R . gprint.dmm.R . gresponse.R . gresponse.dmm.R . gsummary.R . gsummary.dmm.R . gsummary_specific.R . is.cecov.R . is.crossclass.R . is.specific.R . is.var.R . is.withinclass.R . make.cohort.R . make.countarray.R . make.csummarytables.R . make.ctable.R . make.dmmobj.R . make.gsummarytables.R . make.matcline.R . make.patyline.R . match.cecov.nonspecific.R . match.cecov.specific.R . match.var.specific.R . mdf.R . part.add.R . partocov.R . pedcheck.R . pedrenum.R . permpaste.R . phenclasses.R . plot.dmm.R . print.csummary.dmm.R . print.csummarytables.dmm.R . print.csumspecific.dmm.R . print.dmm.R . print.gresponse.dmm.R . print.gsummary.dmm.R . print.gsummarytables.dmm.R . print.gsumspecific.dmm.R . print.summary.dmm.R . selfpaste.R . separ.R . siga.posdef.R . siga.posdef.specific.R . sigatoie.R . sigatovc.R . summary.dmm.R . summary.gresponse.dmm.R . traitpairstotraits.R . unfactor.R . varlz.R . varz.R . vt.R . warcolak.convert.R .  Full dmm package functions and examples
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