ó áp7]c@s½dZddlmZddlZddlmZd„Zed„Z d„Z e d„Z d „Z d „Zd „Zd „Zd „Zd„Zd„Zed„Zd„Zd„ZdS(sôhelper functions conversion between moments contains: * conversion between central and non-central moments, skew, kurtosis and cummulants * cov2corr : convert covariance matrix to correlation matrix Author: Josef Perktold License: BSD-3 iÿÿÿÿ(trangeN(tcombcCsOtt|tƒt|tƒgƒr1tj|ƒSt|tjƒrG|S|SdS(N(tanyt isinstancetlistttupletnptarraytndarray(tx((s?lib/python2.7/site-packages/statsmodels/stats/moment_helpers.pyt_convert_to_multidims $ cCs&t|jƒdkr||ƒS|jS(Ni(tlentshapetT(R ttotype((s?lib/python2.7/site-packages/statsmodels/stats/moment_helpers.pyt_convert_from_multidims cCs4t|ƒ}d„}tj|d|ƒ}t|ƒS(swconvert central to non-central moments, uses recursive formula optionally adjusts first moment to return mean c SsÁ|d}dgt|ƒ}d|dconvert central moments to mean, variance, skew, kurtosis c Ss€|\}}}}|}|||}|d|||d}|d||d||||d}t||||fƒS(Niii(R<( R,RR5R7R9RR2R6R8((s?lib/python2.7/site-packages/statsmodels/stats/moment_helpers.pyRÍs *i(R RRRR(R,R"RR((s?lib/python2.7/site-packages/statsmodels/stats/moment_helpers.pytmnc2mvskÈs  cCsUtj|ƒ}tjtj|ƒƒ}|tj||ƒ}|rM||fS|SdS(s/ convert covariance matrix to correlation matrix Parameters ---------- cov : array_like, 2d covariance matrix, see Notes Returns ------- corr : ndarray (subclass) correlation matrix return_std : bool If this is true then the standard deviation is also returned. By default only the correlation matrix is returned. Notes ----- This function does not convert subclasses of ndarrays. This requires that division is defined elementwise. np.ma.array and np.matrix are allowed. N(Rt asanyarraytsqrttdiagtouter(tcovt return_stdtstd_tcorr((s?lib/python2.7/site-packages/statsmodels/stats/moment_helpers.pytcov2corrçs  cCs8tj|ƒ}tj|ƒ}|tj||ƒ}|S(só convert correlation matrix to covariance matrix given standard deviation Parameters ---------- corr : array_like, 2d correlation matrix, see Notes std : array_like, 1d standard deviation Returns ------- cov : ndarray (subclass) covariance matrix Notes ----- This function does not convert subclasses of ndarrays. This requires that multiplication is defined elementwise. np.ma.array are allowed, but not matrices. (RR>RA(REtstdRDRB((s?lib/python2.7/site-packages/statsmodels/stats/moment_helpers.pytcorr2covscCstjtj|ƒƒS(s get standard deviation from covariance matrix just a shorthand function np.sqrt(np.diag(cov)) Parameters ---------- cov : array_like, square covariance matrix Returns ------- std : ndarray standard deviation from diagonal of cov (RR?R@(RB((s?lib/python2.7/site-packages/statsmodels/stats/moment_helpers.pytse_cov#s(t__doc__tstatsmodels.compat.pythonRtnumpyRt scipy.specialRR RRRRR#R&R(R*R1R:R<R=tFalseRFRHRI(((s?lib/python2.7/site-packages/statsmodels/stats/moment_helpers.pyt s"