statsmodels.stats.weightstats.CompareMeans.ttest_ind CompareMeans.ttest_ind(alternative='two-sided', usevar='pooled', value=0) [source] ttest for the null hypothesis of identical means this should also be the same as onewaygls, except for ddof differences Parameters: x1, x2 : array_like, 1-D or 2-D two independent samples, see notes for 2-D case alternative : string The alternative hypothesis, H1, has to be one of the following ?two-sided?: H1: difference in means not equal to value (def

statsmodels.stats.weightstats.CompareMeans.dof_satt CompareMeans.dof_satt() [source] degrees of freedom of Satterthwaite for unequal variance

statsmodels.stats.diagnostic.CompareCox.run CompareCox.run(results_x, results_z, attach=True) run Cox test for non-nested models Parameters: results_x : Result instance result instance of first model results_z : Result instance result instance of second model attach : bool If true, then the intermediate results are attached to the instance. Returns: tstat : float t statistic for the test that including the fitted values of the first model in the second model has no effect. pvalue

statsmodels.stats.diagnostic.CompareJ.run CompareJ.run(results_x, results_z, attach=True) run J-test for non-nested models Parameters: results_x : Result instance result instance of first model results_z : Result instance result instance of second model attach : bool If true, then the intermediate results are attached to the instance. Returns: tstat : float t statistic for the test that including the fitted values of the first model in the second model has no effect. pvalue : floa

statsmodels.genmod.families.links.CLogLog.inverse_deriv CLogLog.inverse_deriv(z) [source] Derivative of the inverse of the C-Log-Log transform link function Parameters: z : array-like The value of the inverse of the CLogLog link function at p Returns: The derivative of the inverse of the CLogLog link function :

statsmodels.genmod.families.links.CLogLog.deriv2 CLogLog.deriv2(p) Second derivative of the link function g??(p) implemented through numerical differentiation

statsmodels.genmod.families.links.CLogLog.inverse CLogLog.inverse(z) [source] Inverse of C-Log-Log transform link function Parameters: z : array-like The value of the inverse of the CLogLog link function at p Returns: p : array Mean parameters Notes g^(-1)(z) = 1-exp(-exp(z))

statsmodels.genmod.families.links.CDFLink.inverse_deriv CDFLink.inverse_deriv(z) [source] Derivative of the inverse of the CDF transformation link function Parameters: z : array The inverse of the link function at p Returns: The value of the derivative of the inverse of the logit function :

statsmodels.genmod.families.links.CLogLog.deriv CLogLog.deriv(p) [source] Derivative of C-Log-Log transform link function Parameters: p : array-like Mean parameters Returns: g?(p) : array The derivative of the CLogLog transform link function Notes g?(p) = - 1 / (log(p) * p)

statsmodels.genmod.families.links.CDFLink.inverse CDFLink.inverse(z) [source] The inverse of the CDF link Parameters: z : array-like The value of the inverse of the link function at p Returns: p : array Mean probabilities. The value of the inverse of CDF link of z Notes g^(-1)(z) = dbn.cdf(z)