statsmodels.discrete.discrete_model.MultinomialModel.predict¶

MultinomialModel.predict(params, exog=None, which='mean', linear=None)[source]¶

Predict response variable of a model given exogenous variables.

Parameters:¶

paramsarray_like

2d array of fitted parameters of the model. Should be in the order returned from the model.

exogarray_like

1d or 2d array of exogenous values. If not supplied, the whole exog attribute of the model is used. If a 1d array is given it assumed to be 1 row of exogenous variables. If you only have one regressor and would like to do prediction, you must provide a 2d array with shape[1] == 1.

which{‘mean’, ‘linear’, ‘var’, ‘prob’}, optional

Statistic to predict. Default is ‘mean’.

• ‘mean’ returns the conditional expectation of endog E(y | x), i.e. exp of linear predictor.

• ‘linear’ returns the linear predictor of the mean function.

• ‘var’ returns the estimated variance of endog implied by the model.

linearbool

If True, returns the linear predicted values. If False or None, then the statistic specified by which will be returned.

Notes

Column 0 is the base case, the rest conform to the rows of params shifted up one for the base case.