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statsmodels.regression.linear_model.GLS.get_distribution

GLS.get_distribution(params, scale, exog=None, dist_class=None)

Returns a random number generator for the predictive distribution.

Parameters:

params : array-like

The model parameters (regression coefficients).

scale : scalar

The variance parameter.

exog : array-like

The predictor variable matrix.

dist_class : class

A random number generator class. Must take ‘loc’ and ‘scale’ as arguments and return a random number generator implementing an rvs method for simulating random values. Defaults to Gaussian.

Returns a frozen random number generator object with mean and :

variance determined by the fitted linear model. 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.

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