statsmodels.sandbox.tsa.fftarma.ArmaFft.spd ArmaFft.spd(npos) [source] raw spectral density, returns Fourier transform n is number of points in positive spectrum, the actual number of points is twice as large. different from other spd methods with fft

statsmodels.tsa.vector_ar.dynamic.DynamicVAR.resid static DynamicVAR.resid() [source]

statsmodels.sandbox.distributions.extras.NormExpan_gen.est_loc_scale NormExpan_gen.est_loc_scale(*args, **kwds) est_loc_scale is deprecated! This function is deprecated, use self.fit_loc_scale(data) instead.

statsmodels.regression.linear_model.RegressionResults.bic static RegressionResults.bic() [source]

statsmodels.discrete.discrete_model.DiscreteResults.t_test DiscreteResults.t_test(r_matrix, cov_p=None, scale=None, use_t=None) Compute a t-test for a each linear hypothesis of the form Rb = q Parameters: r_matrix : array-like, str, tuple array : If an array is given, a p x k 2d array or length k 1d array specifying the linear restrictions. It is assumed that the linear combination is equal to zero. str : The full hypotheses to test can be given as a string. See the examples. tuple : A tup

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

statsmodels.stats.weightstats._tstat_generic statsmodels.stats.weightstats._tstat_generic(value1, value2, std_diff, dof, alternative, diff=0) [source] generic ttest to save typing

statsmodels.sandbox.distributions.extras.NormExpan_gen.expect NormExpan_gen.expect(func=None, args=(), loc=0, scale=1, lb=None, ub=None, conditional=False, **kwds) Calculate expected value of a function with respect to the distribution. The expected value of a function f(x) with respect to a distribution dist is defined as: ubound E[x] = Integral(f(x) * dist.pdf(x)) lbound Parameters: func : callable, optional Function for which integral is calculated. Takes only one argum

statsmodels.sandbox.distributions.extras.NormExpan_gen.entropy NormExpan_gen.entropy(*args, **kwds) Differential entropy of the RV. Parameters: arg1, arg2, arg3,... : array_like The shape parameter(s) for the distribution (see docstring of the instance object for more information). loc : array_like, optional Location parameter (default=0). scale : array_like, optional Scale parameter (default=1).

statsmodels.tsa.vector_ar.irf.IRAnalysis.lr_effect_stderr IRAnalysis.lr_effect_stderr(orth=False) [source]