Module Expr Str ImportFrom alias Import alias identifier Import alias identifier Assign NameStore Call AttributeLoad AttributeLoad AttributeLoad NameLoad attr attr attr Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr Expr Call NameLoad Call AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr ListLoad Num ListLoad Num Expr Call NameLoad NameLoad Assign NameStore Call AttributeLoad NameLoad attr ListLoad Num ListLoad Num Expr Call NameLoad NameLoad Assign NameStore Call AttributeLoad NameLoad attr Num Num Num Expr Call NameLoad NameLoad
N/A N/A 
This script provides a tutorial on how to use estimate and conduct
inference in an accelerated failure time model using empirical likelihood.

We will be using the Stanford Heart Transplant data

 __future__ print_function N/A statsmodels.api sm N/A numpy np N/A data N/A N/A N/A N/A sm datasets heart load N/A model N/A N/A N/A sm emplike emplikeAFT N/A N/A np log10 N/A data endog N/A N/A sm add_constant N/A data exog N/A data censors N/A fitted N/A N/A model fit N/A N/A print N/A N/A fitted params N/A test1 N/A N/A fitted test_beta N/A 4 N/A 0 N/A N/A print test1 N/A test2 N/A N/A fitted test_beta N/A -0.05 N/A 1 N/A N/A print test2 N/A ci_beta1 N/A N/A fitted ci_beta 1 0.1 -0.1 N/A N/A print ci_beta1