Estimating sampling error of evolutionary statistics based on genetic covariance matrices using maximum likelihood

  title={Estimating sampling error of evolutionary statistics based on genetic covariance matrices using maximum likelihood},
  author={David Houle and Karin Meyer},
  journal={Journal of Evolutionary Biology},
  • D. Houle, K. Meyer
  • Published 1 August 2015
  • Mathematics
  • Journal of Evolutionary Biology
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… 
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