statsmodels.sandbox.distributions.transformed.Transf_gen.nnlf Transf_gen.nnlf(theta, x) Return negative loglikelihood function Notes This is -sum(log pdf(x, theta), axis=0) where theta are the parameters (including loc and scale).

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.miscmodels.tmodel.TLinearModel.initialize TLinearModel.initialize() [source]

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

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

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

statsmodels.tsa.ar_model.ARResults.remove_data ARResults.remove_data() remove data arrays, all nobs arrays from result and model This reduces the size of the instance, so it can be pickled with less memory. Currently tested for use with predict from an unpickled results and model instance. Warning Since data and some intermediate results have been removed calculating new statistics that require them will raise exceptions. The exception will occur the first time an attribute is accessed that

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.ar_model.ARResults class statsmodels.tsa.ar_model.ARResults(model, params, normalized_cov_params=None, scale=1.0) [source] Class to hold results from fitting an AR model. Parameters: model : AR Model instance Reference to the model that is fit. params : array The fitted parameters from the AR Model. normalized_cov_params : array inv(dot(X.T,X)) where X is the lagged values. scale : float, optional An estimate of the scale of the model. Returns: **Attributes** : aic