statsmodels.regression.mixed_linear_model.MixedLMResults.initialize MixedLMResults.initialize(model, params, **kwd)

statsmodels.sandbox.distributions.transformed.invdnormalg statsmodels.sandbox.distributions.transformed.invdnormalg = a class for non-linear monotonic transformation of a continuous random variable

statsmodels.sandbox.tsa.fftarma.ArmaFft.fftar ArmaFft.fftar(n=None) [source] Fourier transform of AR polynomial, zero-padded at end to n Parameters: n : int length of array after zero-padding Returns: fftar : ndarray fft of zero-padded ar polynomial

statsmodels.regression.quantile_regression.QuantRegResults.tvalues static QuantRegResults.tvalues() Return the t-statistic for a given parameter estimate.

statsmodels.sandbox.regression.gmm.IVRegressionResults.initialize IVRegressionResults.initialize(model, params, **kwd)

statsmodels.discrete.discrete_model.CountResults.llnull static CountResults.llnull()

statsmodels.robust.scale.stand_mad statsmodels.robust.scale.stand_mad(a, c=0.67448975019608171, axis=0) [source]

statsmodels.stats.weightstats.CompareMeans.ztest_ind CompareMeans.ztest_ind(alternative='two-sided', usevar='pooled', value=0) [source] z-test for the null hypothesis of identical means 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 (default) ?larger? : H1: difference in means larger than value ?smaller? :

statsmodels.sandbox.distributions.transformed.Transf_gen.moment Transf_gen.moment(n, *args, **kwds) n?th order non-central moment of distribution. Parameters: n : int, n>=1 Order of moment. arg1, arg2, arg3,... : float The shape parameter(s) for the distribution (see docstring of the instance object for more information). kwds : keyword arguments, optional These can include ?loc? and ?scale?, as well as other keyword arguments relevant for a given distribution.

statsmodels.discrete.discrete_model.ProbitResults.llr_pvalue static ProbitResults.llr_pvalue()