A simple algorithm to estimate genetic variance in an animal threshold model using Bayesian inference
Publication details
Journal : Genetics Selection Evolution , vol. 42 , p. 7 , 2010
International Standard Numbers
:
Printed
:
0999-193X
Electronic
:
1297-9686
Publication type : Academic article
Issue : 29
Links
:
OMTALE
:
http://www.gsejournal.org/cont...
DOI
:
doi.org/10.1186/1297-9686-42-2...
If you have questions about the publication, you may contact Nofima’s Chief Librarian.
Kjetil Aune
Chief Librarian
kjetil.aune@nofima.no
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.