statsmodels.genmod.families.links.nbinom.inverse_deriv nbinom.inverse_deriv(z) Derivative of the inverse of the negative binomial transform Parameters: z : array-like Usually the linear predictor for a GLM or GEE model Returns: The value of the inverse of the derivative of the negative binomial : link :

statsmodels.discrete.discrete_model.MNLogit.fit_regularized MNLogit.fit_regularized(start_params=None, method='l1', maxiter='defined_by_method', full_output=1, disp=1, callback=None, alpha=0, trim_mode='auto', auto_trim_tol=0.01, size_trim_tol=0.0001, qc_tol=0.03, **kwargs) Fit the model using a regularized maximum likelihood. The regularization method AND the solver used is determined by the argument method. Parameters: start_params : array-like, optional Initial guess of the solution for

statsmodels.tsa.vector_ar.var_model.VARProcess.plot_acorr VARProcess.plot_acorr(nlags=10, linewidth=8) [source] Plot theoretical autocorrelation function

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.NegativeBinomialResults.normalized_cov_params NegativeBinomialResults.normalized_cov_params()

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