A simple algorithm to estimate genetic variance in an animal threshold model using Bayesian inference

Summary

Conclusions: The new algorithm to estimate genetic parameters via Gibbs sampling solves the bias problems typically occurring in animal threshold model analysis of binary traits with one observation per animal. Furthermore, the method considerably speeds up mixing properties of the Gibbs sampler with respect to genetic parameters, which would be an advantage of any linear or non-linear animal model.

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DOI : doi.org/10.1186/1297-9686-42-2...
SAMMENDRAG : http://www.gsejournal.org/cont...
OMTALE : http://www.gsejournal.org/cont...