statsmodels.tsa.vector_ar.var_model.VARResults.fittedvalues static VARResults.fittedvalues() [source] The predicted insample values of the response variables of the model.

statsmodels.discrete.discrete_model.NegativeBinomialResults.pvalues static NegativeBinomialResults.pvalues()

statsmodels.miscmodels.count.PoissonZiGMLE.predict PoissonZiGMLE.predict(params, exog=None, *args, **kwargs) After a model has been fit predict returns the fitted values. This is a placeholder intended to be overwritten by individual models.

statsmodels.robust.robust_linear_model.RLM.initialize RLM.initialize() Initialize (possibly re-initialize) a Model instance. For instance, the design matrix of a linear model may change and some things must be recomputed.

statsmodels.sandbox.regression.gmm.GMM.fitgmm GMM.fitgmm(start, weights=None, optim_method='bfgs', optim_args=None) [source] estimate parameters using GMM Parameters: start : array_like starting values for minimization weights : array weighting matrix for moment conditions. If weights is None, then the identity matrix is used Returns: paramest : array estimated parameters Notes todo: add fixed parameter option, not here ??? uses scipy.optimize.fmin

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

statsmodels.stats.proportion.binom_tost statsmodels.stats.proportion.binom_tost(count, nobs, low, upp) [source] exact TOST test for one proportion using binomial distribution Parameters: count : integer or array_like the number of successes in nobs trials. nobs : integer the number of trials or observations. low, upp : floats lower and upper limit of equivalence region Returns: pvalue : float p-value of equivalence test pval_low, pval_upp : floats p-values of lower and upper one-

statsmodels.robust.norms.TukeyBiweight class statsmodels.robust.norms.TukeyBiweight(c=4.685) [source] Tukey?s biweight function for M-estimation. Parameters: c : float, optional The tuning constant for Tukey?s Biweight. The default value is c = 4.685. Notes Tukey?s biweight is sometime?s called bisquare. Methods psi(z) The psi function for Tukey?s biweight estimator psi_deriv(z) The derivative of Tukey?s biweight psi function rho(z) The robust criterion function for Tukey?s biweight e

statsmodels.tsa.arima_model.ARMAResults.hqic static ARMAResults.hqic() [source]

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