A Direct Sampler for G-Wishart Variates

@inproceedings{Lenkoski2013ADS,
  title={A Direct Sampler for G-Wishart Variates},
  author={Alex Lenkoski},
  year={2013}
}
The G-Wishart distribution is the conjugate prior for precision matrices that encode the conditional independencies of a Gaussian graphical model. While the distribution has received considerable attention, posterior inference has proven computationally challenging, in part due to the lack of a direct sampler. In this note, we rectify this situation. The existence of a direct sampler offers a host of new possibilities for the use of G-Wishart variates. We discuss one such development by… CONTINUE READING

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