statsmodels.stats.moment_helpers.mvsk2mnc statsmodels.stats.moment_helpers.mvsk2mnc(args) [source] convert mean, variance, skew, kurtosis to non-central moments

statsmodels.stats.moment_helpers.mvsk2mc statsmodels.stats.moment_helpers.mvsk2mc(args) [source] convert mean, variance, skew, kurtosis to central moments

statsmodels.stats.moment_helpers.mnc2mc statsmodels.stats.moment_helpers.mnc2mc(mnc, wmean=True) [source] convert non-central to central moments, uses recursive formula optionally adjusts first moment to return mean

statsmodels.stats.moment_helpers.mnc2mvsk statsmodels.stats.moment_helpers.mnc2mvsk(args) [source] convert central moments to mean, variance, skew, kurtosis

statsmodels.stats.moment_helpers.mc2mnc statsmodels.stats.moment_helpers.mc2mnc(mc) [source] convert central to non-central moments, uses recursive formula optionally adjusts first moment to return mean

statsmodels.stats.moment_helpers.mnc2cum statsmodels.stats.moment_helpers.mnc2cum(mnc) [source] convert non-central moments to cumulants recursive formula produces as many cumulants as moments http://en.wikipedia.org/wiki/Cumulant#Cumulants_and_moments

statsmodels.stats.moment_helpers.mc2mvsk statsmodels.stats.moment_helpers.mc2mvsk(args) [source] convert central moments to mean, variance, skew, kurtosis

statsmodels.stats.moment_helpers.cov2corr statsmodels.stats.moment_helpers.cov2corr(cov, return_std=False) [source] 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

statsmodels.stats.moment_helpers.cum2mc statsmodels.stats.moment_helpers.cum2mc(kappa) [source] convert non-central moments to cumulants recursive formula produces as many cumulants as moments References Kenneth Lange: Numerical Analysis for Statisticians, page 40 (http://books.google.ca/books?id=gm7kwttyRT0C&pg=PA40&lpg=PA40&dq=convert+cumulants+to+moments&source=web&ots=qyIaY6oaWH&sig=cShTDWl-YrWAzV7NlcMTRQV6y0A&hl=en&sa=X&oi=book_result&resnum=1&

statsmodels.stats.moment_helpers.corr2cov statsmodels.stats.moment_helpers.corr2cov(corr, std) [source] 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 m