support *kwargs in four deltas
@@ -359,7 +359,8 @@ class Experiment(ExperimentData):
kpis_to_analyse = None,
reference_kpis = {},
weighted_kpis = None,
- deltaWorker = statx.make_delta()):
+ deltaWorker = statx.make_delta(),
+ **kwargs):
"""
Compute delta (with confidence bounds) on all applicable kpis,
and returns in the standard Results format.
@@ -421,7 +422,8 @@ class Experiment(ExperimentData):
spending_function='obrien_fleming',
information_fraction=1,
alpha=0.05,
- cap=8):
+ cap=8,
+ **kwargs):
"""
Calculate the stopping criterion based on the group sequential design
and the effect size.
@@ -472,7 +474,8 @@ class Experiment(ExperimentData):
def bayes_factor_delta(self,
result,
kpis_to_analyse,
- distribution='normal'):
+ distribution='normal',
+ **kwargs):
"""
Calculate the stopping criterion based on the Bayes factor
and the effect size.
@@ -516,7 +519,8 @@ class Experiment(ExperimentData):
result,
kpis_to_analyse,
distribution='normal',
- posterior_width=0.08):
+ posterior_width=0.08,
+ **kwargs):
"""
Calculate the stopping criterion based on the precision of the posterior
and the effect size.
