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# scipy.stats.dirichlet

`scipy.stats.``dirichlet` = <scipy.stats._multivariate.dirichlet_gen object>

  A Dirichlet random variable.

  The `alpha` keyword specifies the concentration parameters of the distribution.

  New in version 0.15.0.

  Parameters:

  x : array_like

  > Quantiles, with the last axis of x denoting the components.

  alpha : array_like

  > The concentration parameters. The number of entries determines the dimensionality of the distribution.

  random_state : None or int or np.random.RandomState instance, optional

  > If int or RandomState, use it for drawing the random variates. If None (or np.random), the global np.random state is used. Default is None.

  Alternatively, the object may be called (as a function) to fix

  concentration parameters, returning a “frozen” Dirichlet

  random variable:

  rv = dirichlet(alpha)

  > - Frozen object with the same methods but holding the given concentration parameters fixed.

  Notes

  Each \(\alpha\) entry must be positive. The distribution has only support on the simplex defined by

  \[\sum_{i=1}^{K} x_i \le 1\]

  The probability density function for `dirichlet` is

  \[f(x) = \frac{1}{\mathrm{B}(\boldsymbol\alpha)} \prod_{i=1}^K x_i^{\alpha_i - 1}\]

  where

  \[\mathrm{B}(\boldsymbol\alpha) = \frac{\prod_{i=1}^K \Gamma(\alpha_i)} {\Gamma\bigl(\sum_{i=1}^K \alpha_i\bigr)}\]

  and \(\boldsymbol\alpha=(\alpha_1,\ldots,\alpha_K)\), the concentration parameters and \(K\) is the dimension of the space where \(x\) takes values.

  Note that the dirichlet interface is somewhat inconsistent. The array returned by the rvs function is transposed with respect to the format expected by the pdf and logpdf.

  Methods

  `pdf(x, alpha)` | Probability density function.
  `logpdf(x, alpha)` | Log of the probability density function.
  `rvs(alpha, size=1, random_state=None)` | Draw random samples from a Dirichlet distribution.
  `mean(alpha)` | The mean of the Dirichlet distribution
  `var(alpha)` | The variance of the Dirichlet distribution
  `entropy(alpha)` | Compute the differential entropy of the Dirichlet distribution.