GLS.get_distribution()

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.