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:

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

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. 


    © 2009–2012 Statsmodels Developers© 2006–2008 Scipy Developers
{'path': 'public/docs/statsmodels/generated/statsmodels.regression.linear_model.gls.get_distribution.html', 'source': 'DevDocs.IO'}