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The von Mises-Fisher distribution is a probability distribution on the ($p-1$)-sphere. I'm interested in the efficient generation of this distribution for a relatively high dimension ($1000$ or greater) for application in a search step in a meta-heuristic.

¿Is there a numerical algorithm to efficiently generate such a distribution?

I'll be sampling a lot of vectors, so I'm more interested in efficiency that exactitude. I could use some approximation, or any other easily generated distribution that allows me to select a direction with a mean and a concentration parameter, similar to von Mises-Fisher.

Thanks in advance.

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Have you seen this? – J. M. Jul 11 '12 at 15:49
Seems what I'm looking for but sadly I'm on a forbidden country (Cuba) and almost never (like zero-probability) have access to online paying services. Thanks for the link anyway, you have my upvote. – Alejandro Piad Jul 13 '12 at 12:52

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