Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/18906
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Houle, D | en |
dc.contributor.author | Meyer, Karin | en |
dc.date.accessioned | 2016-04-22T15:38:00Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Journal of Evolutionary Biology, 28(8), p. 1542-1549 | en |
dc.identifier.issn | 1420-9101 | en |
dc.identifier.issn | 1010-061X | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/18906 | - |
dc.description.abstract | We explore the estimation of uncertainty in evolutionary parameters using a recently devised approach for resampling entire additive genetic variance- covariance matrices (G). Large-sample theory shows that maximum-likelihood estimates (including restricted maximum likelihood, REML) asymptotically have a multivariate normal distribution, with covariance matrix derived from the inverse of the information matrix, and mean equal to the estimated G. This suggests that sampling estimates of G from this distribution can be used to assess the variability of estimates of G, and of functions of G. We refer to this as the REML-MVN method. This has been implemented in the mixed-model program WOMBAT. Estimates of sampling variances from REML-MVN were compared to those from the parametric bootstrap and from a Bayesian Markov chain Monte Carlo (MCMC) approach (implemented in the R package MCMCglmm). We apply each approach to evolvability statistics previously estimated for a large, 20-dimensional data set for Drosophila wings. REML-MVN and MCMC sampling variances are close to those estimated with the parametric bootstrap. Both slightly underestimate the error in the best-estimated aspects of the G matrix. REML analysis supports the previous conclusion that the G matrix for this population is full rank. REML-MVN is computationally very efficient, making it an attractive alternative to both data resampling and MCMC approaches to assessing confidence in parameters of evolutionary interest. | en |
dc.language | en | en |
dc.publisher | Wiley-Blackwell Publishing Ltd | en |
dc.relation.ispartof | Journal of Evolutionary Biology | en |
dc.title | Estimating sampling error of evolutionary statistics based on genetic covariance matrices using maximum likelihood | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1111/jeb.12674 | en |
dcterms.accessRights | Gold | en |
dc.subject.keywords | Animal Breeding | en |
local.contributor.firstname | D | en |
local.contributor.firstname | Karin | en |
local.subject.for2008 | 070201 Animal Breeding | en |
local.subject.seo2008 | 830399 Livestock Raising not elsewhere classified | en |
local.profile.school | Animal Genetics and Breeding Unit | en |
local.profile.email | kmeyer@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.identifier.epublicationsrecord | une-20160414-131331 | en |
local.publisher.place | United Kingdom | en |
local.format.startpage | 1542 | en |
local.format.endpage | 1549 | en |
local.identifier.scopusid | 84938974080 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 28 | en |
local.identifier.issue | 8 | en |
local.access.fulltext | Yes | en |
local.contributor.lastname | Houle | en |
local.contributor.lastname | Meyer | en |
dc.identifier.staff | une-id:kmeyer | en |
local.profile.orcid | 0000-0003-2663-9059 | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:19107 | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | Estimating sampling error of evolutionary statistics based on genetic covariance matrices using maximum likelihood | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Houle, D | en |
local.search.author | Meyer, Karin | en |
local.uneassociation | Unknown | en |
local.identifier.wosid | 000359606200010 | en |
local.year.published | 2015 | en |
local.subject.for2020 | 300305 Animal reproduction and breeding | en |
local.subject.seo2020 | 100407 Insects | en |
Appears in Collections: | Animal Genetics and Breeding Unit (AGBU) Journal Article |
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