statsmodels.regression.process_regression.ProcessMLEResults.bootstrap¶
- ProcessMLEResults.bootstrap(nrep=100, method='nm', disp=0, store=1)¶
simple bootstrap to get mean and variance of estimator
see notes
- Parameters:
- Returns:
- mean
ndarray
mean of parameter estimates over bootstrap replications
- std
ndarray
standard deviation of parameter estimates over bootstrap replications
- mean
Notes
This was mainly written to compare estimators of the standard errors of the parameter estimates. It uses independent random sampling from the original endog and exog, and therefore is only correct if observations are independently distributed.
This will be moved to apply only to models with independently distributed observations.