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Tessero\StatsFns

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boxcoxNormmax static 
boxcoxNormmax(array $x, string $method = 'pearsonr'): float

scipy.stats.boxcox_normmax: the Box-Cox parameter lambda that best normalises x.

yeojohnsonNormmax static 
yeojohnsonNormmax(array $x): float

scipy.stats.yeojohnson_normmax: the Yeo-Johnson parameter lambda maximising the log-likelihood.

ppccPlot static 
ppccPlot(array $x, float $a, float $b, int $n = 80): array

scipy.stats.ppcc_plot(x, a, b, dist='tukeylambda', N=80): probability-plot correlation coefficient of the Tukey-lambda family over N shape values linspace(a, b, N).

ppccMax static 
ppccMax(array $x): float
bayesMvs static 
bayesMvs(array $data, float $alpha = 0.9): array

scipy.stats.bayes_mvs: Bayesian (center, (lower, upper)) estimates for the mean, variance and standard deviation of 1-D data under Jeffreys' prior.

mvsdist static 
mvsdist(array $data): array

scipy.stats.mvsdist: the three "frozen" distributions (mean, variance, standard deviation) whose mean() and interval() reproduce {@see bayesMvs}. Returns them in the order (mean, var, std).