statsmodels.genmod.generalized_estimating_equations.GEE.get_distribution

GEE.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:

paramsnumpy:array_like

The model parameters.

scalescalar

The scale parameter.

exognumpy:array_like

The predictor variable matrix.

offsetnumpy:array_like or None

Offset variable for predicted mean.

exposurenumpy:array_like or None

Log(exposure) will be added to the linear prediction.

var_weightsnumpy:array_like

1d array of variance (analytic) weights. The default is None.

n_trialsint

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 with gen.rvs(n) where n is the number of observations in the data set used to fit the model. If any other value is used for n, misleading results will be produced.