# 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. Frozen random number generator object with mean and variance determined by the fitted linear model. Use the rvs method to generate random values. gen

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.