(ph(SrSSKrSSKJr S/rSrg)zVSome more special functions which may be useful for multivariate statistical analysis.N)gammaln multigammalnc $[R"U5n[R"U5(a[R"U5U:wa [ S5e[R "USUS- -:*5(a[ SUSSSUS- -SS35eXS- -S-[R "[R5-nU[R"[[SUS-5Vs/sH o0US - S - - PM sn5S S 9- nU$s snf) ajReturns the log of multivariate gamma, also sometimes called the generalized gamma. Parameters ---------- a : ndarray The multivariate gamma is computed for each item of `a`. d : int The dimension of the space of integration. Returns ------- res : ndarray 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 .. math:: \Gamma_d(a) = \int_{A>0} e^{-tr(A)} |A|^{a - (d+1)/2} dA with the condition :math:`a > (d-1)/2`, and :math:`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 .. math:: \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 -------- >>> import numpy as np >>> 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 z*d should be a positive integer (dimension)g?z condition a (fz) > 0.5 * (d-1) (z ) not metg?g?r)axis) npasarrayisscalarfloor ValueErroranylogpisumloggamrange)adresjs M/var/www/html/venv/lib/python3.13/site-packages/scipy/special/_spfun_stats.pyrr*sp 1 A ;;q>>bhhqkQ.EFF vva3!a%= !!=1->sac{1oYWXX !9t rvvbee} ,C266&E!QqSMBMqBz>MBC! LLC JCs+D )__doc__numpyr scipy.specialrr__all__rrr s#@ +  @r