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

@article{Houle2015EstimatingSE,
  title={Estimating sampling error of evolutionary statistics based on genetic covariance matrices using maximum likelihood},
  author={D. Houle and K. Meyer},
  journal={Journal of Evolutionary Biology},
  year={2015},
  volume={28}
}
  • D. Houle, K. Meyer
  • Published 2015
  • Biology, Medicine
  • 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… Expand
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