scipy.special.multigammaln#
- scipy.special.multigammaln(a, d)[source]#
Returns the log of multivariate gamma, also sometimes called the generalized gamma.
- Parameters
- andarray
The multivariate gamma is computed for each item of a.
- dint
The dimension of the space of integration.
- Returns
- resndarray
The values of the log multivariate gamma at the given points a.
Notes
The formal definition of the multivariate gamma of dimension d for a real a is
\[\Gamma_d(a) = \int_{A>0} e^{-tr(A)} |A|^{a - (d+1)/2} dA\]with the condition \(a > (d-1)/2\), and \(A > 0\) being the set of all the positive definite matrices of dimension d. Note that a is a scalar: the integrand only is multivariate, the argument is not (the function is defined over a subset of the real set).
This can be proven to be equal to the much friendlier equation
\[\Gamma_d(a) = \pi^{d(d-1)/4} \prod_{i=1}^{d} \Gamma(a - (i-1)/2).\]References
R. J. Muirhead, Aspects of multivariate statistical theory (Wiley Series in probability and mathematical statistics).
Examples
>>> from scipy.special import multigammaln, gammaln >>> a = 23.5 >>> d = 10 >>> multigammaln(a, d) 454.1488605074416
Verify that the result agrees with the logarithm of the equation shown above:
>>> d*(d-1)/4*np.log(np.pi) + gammaln(a - 0.5*np.arange(0, d)).sum() 454.1488605074416