statsmodels.regression.linear_model.OLS.get_distribution

OLS.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.