Draw samples from the Dirichlet distribution.
Draw size samples of dimension k from a Dirichlet distribution. A Dirichlet-distributed random variable can be seen as a multivariate generalization of a Beta distribution. Dirichlet pdf is the conjugate prior of a multinomial in Bayesian inference.
Parameters : | alpha : array
size : array
|
---|
Notes
X \approx \prod_{i=1}^{k}{x^{\alpha_i-1}_i}
Uses the following property for computation: for each dimension, draw a random sample y_i from a standard gamma generator of shape alpha_i, then X = \frac{1}{\sum_{i=1}^k{y_i}} (y_1, \ldots, y_n) is Dirichlet distributed.
References
[R224] | David McKay, “Information Theory, Inference and Learning Algorithms,” chapter 23, http://www.inference.phy.cam.ac.uk/mackay/ |