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|Title:||Up hill, down dale: quantitative genetics of curvaceous traits||Contributor(s):||Meyer, K (author); Kirkpatrick, M (author)||Publication Date:||2005||DOI:||10.1098/rstb.2005.1681||Handle Link:||https://hdl.handle.net/1959.11/669||Abstract:||'Repeated' measurements for a trait and individual, taken along some continuous scale such as time, can be thought of as representing points on a curve, where both means and covariances along the trajectory can change, gradually and continually. Such traits are commonly referred to as 'function-valued' (FV) traits. This review shows that standard quantitative genetic concepts extend readily to FV traits, with individual statistics, such as estimated breeding values and selection response, replaced by corresponding curves, modelled by respective functions. Covariance functions are introduced as the FV equivalent to matrices of covariances.Considering the class of functions represented by a regression on the continuous covariable, FV traits can be analysed within the linear mixed model framework commonly employed in quantitative genetics, giving rise to the so-called random regression model. Estimation of covariance functions, either indirectly from estimated covariances or directly from the data using restricted maximum likelihood or Bayesian analysis, is considered. It is shown that direct estimation of the leading principal components of covariance functions is feasible and advantageous. Extensions to multidimensional analyses are discussed.||Publication Type:||Journal Article||Source of Publication:||Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1459), p. 1443-1455||Publisher:||The Royal Society Publishing||Place of Publication:||United Kingdom||ISSN:||0962-8436||Field of Research (FOR):||070201 Animal Breeding||Peer Reviewed:||Yes||HERDC Category Description:||C1 Refereed Article in a Scholarly Journal||Statistics to Oct 2018:||Visitors: 104
|Appears in Collections:||Journal Article|
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