statsmodels.miscmodels.count.PoissonOffsetGMLE.information PoissonOffsetGMLE.information(params) Fisher information matrix of model Returns -Hessian of loglike evaluated at params.

statsmodels.regression.linear_model.RegressionResults.compare_lr_test RegressionResults.compare_lr_test(restricted, large_sample=False) [source] Likelihood ratio test to test whether restricted model is correct Parameters: restricted : Result instance The restricted model is assumed to be nested in the current model. The result instance of the restricted model is required to have two attributes, residual sum of squares, ssr, residual degrees of freedom, df_resid. large_sample : bool Flag

statsmodels.sandbox.regression.gmm.IVRegressionResults.cov_HC1 static IVRegressionResults.cov_HC1() See statsmodels.RegressionResults

statsmodels.genmod.generalized_linear_model.GLMResults.resid_pearson static GLMResults.resid_pearson() [source]

statsmodels.sandbox.distributions.transformed.TransfTwo_gen.moment TransfTwo_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.miscmodels.tmodel.TLinearModel.initialize TLinearModel.initialize() [source]

statsmodels.discrete.discrete_model.CountResults.initialize CountResults.initialize(model, params, **kwd)

statsmodels.tsa.arima_model.ARMAResults.cov_params ARMAResults.cov_params() [source]

statsmodels.miscmodels.count.PoissonGMLE.nloglike PoissonGMLE.nloglike(params)

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