statsmodels.gam.generalized_additive_model.GLMGam.get_distribution¶
- GLMGam.get_distribution(params, scale=None, exog=None, exposure=None, offset=None, var_weights=1.0, n_trials=1.0)¶
Return a instance of the predictive distribution.
- Parameters:
- paramsarray_like
The model parameters.
- scalescalar
The scale parameter.
- exogarray_like
The predictor variable matrix.
- offsetarray_like or
None
Offset variable for predicted mean.
- exposurearray_like or
None
Log(exposure) will be added to the linear prediction.
- var_weightsarray_like
1d array of variance (analytic) weights. The default is None.
- n_trials
int
Number of trials for the binomial distribution. The default is 1 which corresponds to a Bernoulli random variable.
- Returns:
gen
Instance of a scipy frozen distribution based on estimated parameters. Use the
rvs
method to generate random values.
Notes
Due to the behavior of
scipy.stats.distributions objects
, the returned random number generator must be called withgen.rvs(n)
wheren
is the number of observations in the data set used to fit the model. If any other value is used forn
, misleading results will be produced.