statsmodels.tsa.arima_model.ARMAResults.tvalues static ARMAResults.tvalues() Return the t-statistic for a given parameter estimate.

statsmodels.regression.linear_model.OLSResults.llf static OLSResults.llf()

statsmodels.duration.hazard_regression.PHRegResults.standard_errors static PHRegResults.standard_errors() [source] Returns the standard errors of the parameter estimates.

statsmodels.tools.tools.clean0 statsmodels.tools.tools.clean0(matrix) [source] Erase columns of zeros: can save some time in pseudoinverse.

statsmodels.discrete.discrete_model.DiscreteModel.hessian DiscreteModel.hessian(params) The Hessian matrix of the model

statsmodels.sandbox.distributions.extras.ACSkewT_gen.expect ACSkewT_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 argument.

statsmodels.tsa.arima_model.ARIMAResults.bse static ARIMAResults.bse()

statsmodels.tsa.vector_ar.var_model.VAR.predict VAR.predict(params, start=None, end=None, lags=1, trend='c') [source] Returns in-sample predictions or forecasts

statsmodels.discrete.discrete_model.NegativeBinomial.cov_params_func_l1 NegativeBinomial.cov_params_func_l1(likelihood_model, xopt, retvals) Computes cov_params on a reduced parameter space corresponding to the nonzero parameters resulting from the l1 regularized fit. Returns a full cov_params matrix, with entries corresponding to zero?d values set to np.nan.

statsmodels.sandbox.regression.gmm.IVRegressionResults.HC1_se static IVRegressionResults.HC1_se() See statsmodels.RegressionResults