On equivalence of the LKJ distribution and the restricted Wishart distribution
Z Wang, Y Wu, H Chu - arXiv preprint arXiv:1809.04746, 2018 - arxiv.org
Z Wang, Y Wu, H Chu
arXiv preprint arXiv:1809.04746, 2018•arxiv.orgIn this paper, we want to show the Restricted Wishart distribution is equivalent to the LKJ
distribution, which is one way to specify a uniform distribution from the space of positive
definite correlation matrices. Based on this theorem, we propose a new method to generate
random correlation matrices from the LKJ distribution. This new method is faster than the
original onion method for generating random matrices, especially in the low dimension ($ T<
120$) situation.
distribution, which is one way to specify a uniform distribution from the space of positive
definite correlation matrices. Based on this theorem, we propose a new method to generate
random correlation matrices from the LKJ distribution. This new method is faster than the
original onion method for generating random matrices, especially in the low dimension ($ T<
120$) situation.
In this paper, we want to show the Restricted Wishart distribution is equivalent to the LKJ distribution, which is one way to specify a uniform distribution from the space of positive definite correlation matrices. Based on this theorem, we propose a new method to generate random correlation matrices from the LKJ distribution. This new method is faster than the original onion method for generating random matrices, especially in the low dimension () situation.
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