4.1.7. statsmodels.base.model

4.1.7.1. Functions

approx_fprime(x, f[, epsilon, args, kwargs, ...])	Gradient of function, or Jacobian if function f returns 1d array
handle_data(endog, exog[, missing, hasconst])
handle_formula_data(Y, X, formula[, depth, ...])	Returns endog, exog, and the model specification from arrays and formula
iterkeys(obj, **kwargs)
nan_dot(A, B)	Returns np.dot(left_matrix, right_matrix) with the convention that nan * 0 = 0 and nan * x = nan if x != 0.
recipr(X)	Return the reciprocal of an array, setting all entries less than or equal to 0 to 0.

4.1.7.2. Classes

ContrastResults([t, F, sd, effect, ...])	Class for results of tests of linear restrictions on coefficients in a model.
GenericLikelihoodModel(endog[, exog, ...])	Allows the fitting of any likelihood function via maximum likelihood.
GenericLikelihoodModelResults(model, mlefit)	A results class for the discrete dependent variable models.
LikelihoodModel(endog[, exog])	Likelihood model is a subclass of Model.
LikelihoodModelResults(model, params[, ...])	Class to contain results from likelihood models
LikelihoodResultsWrapper(results)
Model(endog[, exog])	A (predictive) statistical model.
Optimizer
ResultMixin
Results(model, params, **kwd)	Class to contain model results
resettable_cache	alias of ResettableCache