def _check_values(df, stop_times_events):
# check_for_overlapping_intervals(df) # this is currenty too slow for production.
check_low_var(df)
check_complete_separation_low_variance(df, stop_times_events['event'])
pass_for_numeric_dtypes_or_raise(df)
check_for_immediate_deaths(stop_times_events)
check_for_instantaneous_events(stop_times_events)
def _check_values(df, T, E):
pass_for_numeric_dtypes_or_raise(df)
check_nans_or_infs(T)
check_nans_or_infs(E)
check_nans_or_infs(df)
check_low_var(df)
check_complete_separation(df, E, T)
def _check_values(self, df, events, start, stop):
# check_for_overlapping_intervals(df) # this is currently too slow for production.
check_nans_or_infs(df)
check_low_var(df)
check_complete_separation_low_variance(df, events, self.event_col)
check_for_numeric_dtypes_or_raise(df)
check_for_immediate_deaths(events, start, stop)
check_for_instantaneous_events(start, stop)
def _check_values(self, df, events, start, stop):
# check_for_overlapping_intervals(df) # this is currently too slow for production.
check_nans_or_infs(df)
check_low_var(df)
check_complete_separation_low_variance(df, events, self.event_col)
check_for_numeric_dtypes_or_raise(df)
check_for_immediate_deaths(events, start, stop)
check_for_instantaneous_events(start, stop)
def _check_values(self, df, T, E, event_col):
check_for_numeric_dtypes_or_raise(df)
check_nans_or_infs(T)
check_nans_or_infs(E)
check_nans_or_infs(df)
check_complete_separation(df, E, T, event_col)
if self.fit_intercept:
check_low_var(df)
def _check_values(df, E):
# check_for_overlapping_intervals(df) # this is currenty too slow for production.
check_low_var(df)
check_complete_separation(df, E)
pass_for_numeric_dtypes_or_raise(df)
def _check_values(df, E):
# check_for_overlapping_intervals(df) # this is currenty too slow for production.
check_low_var(df)
check_complete_separation_low_variance(df, E)
pass_for_numeric_dtypes_or_raise(df)
def _check_values(df, E):
check_low_var(df)
check_complete_separation(df, E)
pass_for_numeric_dtypes_or_raise(df)
def _check_values(df, E):
check_low_var(df)
check_complete_separation(df, E)
pass_for_numeric_dtypes_or_raise(df)
def _check_values(df, E):
deaths = E == 1
check_low_var(df)
check_low_var(df.loc[deaths], "Complete seperation possibly detected. ", " See https://stats.idre.ucla.edu/other/mult-pkg/faq/general/faqwhat-is-complete-or-quasi-complete-separation-in-logisticprobit-regression-and-how-do-we-deal-with-them/")
check_low_var(df.loc[~deaths], "Complete seperation possibly detected. ", " See https://stats.idre.ucla.edu/other/mult-pkg/faq/general/faqwhat-is-complete-or-quasi-complete-separation-in-logisticprobit-regression-and-how-do-we-deal-with-them/")
pass_for_numeric_dtypes_or_raise(df)
