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.regression.linear_model.OLSResults.pvalues static OLSResults.pvalues()

statsmodels.regression.linear_model.RegressionResults.HC2_se static RegressionResults.HC2_se() [source] See statsmodels.RegressionResults

statsmodels.regression.linear_model.OLSResults.load classmethod OLSResults.load(fname) load a pickle, (class method) Parameters: fname : string or filehandle fname can be a string to a file path or filename, or a filehandle. Returns: unpickled instance :

statsmodels.tsa.arima_model.ARMAResults.summary2 ARMAResults.summary2(title=None, alpha=0.05, float_format='%.4f') [source] Experimental summary function for ARIMA Results Parameters: title : string, optional Title for the top table. If not None, then this replaces the default title alpha : float significance level for the confidence intervals float_format: string : print format for floats in parameters summary Returns: smry : Summary instance This holds the summary table and text,

statsmodels.sandbox.tsa.fftarma.ArmaFft.filter ArmaFft.filter(x) [source] filter a timeseries with the ARMA filter padding with zero is missing, in example I needed the padding to get initial conditions identical to direct filter Initial filtered observations differ from filter2 and signal.lfilter, but at end they are the same. See also tsa.filters.fftconvolve

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

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()