Performance of Hamiltonian Monte Carlo and No-U-Turn Sampler for estimating genetic parameters and breeding values
Abstract Background Hamiltonian Monte Carlo is one of the algorithms of the Markov chain Monte Carlo method that uses Hamiltonian dynamics to propose samples that follow a target distribution. The method can avoid the random walk behavior to achieve a more effective and consistent exploration of the...
| Main Authors: | , |
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| Format: | Article |
| Language: | deu |
| Published: |
BMC
2019-12-01
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| Series: | Genetics Selection Evolution |
| Online Access: | https://doi.org/10.1186/s12711-019-0515-1 |