def __init__(
self,
treatment_grid_num=10,
lower_grid_constraint=0.01,
upper_grid_constraint=0.99,
bootstrap_draws=500,
bootstrap_replicates=100,
spline_order=3,
n_splines=5,
lambda_=0.5,
max_iter=100,
random_seed=None,
verbose=False,
):
self.treatment_grid_num = treatment_grid_num
self.lower_grid_constraint = lower_grid_constraint
self.upper_grid_constraint = upper_grid_constraint
self.bootstrap_draws = bootstrap_draws
self.bootstrap_replicates = bootstrap_replicates
self.spline_order = spline_order
self.n_splines = n_splines
self.lambda_ = lambda_
self.max_iter = max_iter
self.random_seed = random_seed
self.verbose = verbose
# Validate the params
self._validate_init_params()
rand_seed_wrapper()
if self.verbose:
print("Using the following params for the mediation analysis:")
pprint(self.get_params(), indent=4)
def __init__(
self,
gps_family=None,
treatment_grid_num=100,
lower_grid_constraint=0.01,
upper_grid_constraint=0.99,
spline_order=3,
n_splines=30,
lambda_=0.5,
max_iter=100,
random_seed=None,
verbose=False,
):
self.gps_family = gps_family
self.treatment_grid_num = treatment_grid_num
self.lower_grid_constraint = lower_grid_constraint
self.upper_grid_constraint = upper_grid_constraint
self.spline_order = spline_order
self.n_splines = n_splines
self.lambda_ = lambda_
self.max_iter = max_iter
self.random_seed = random_seed
self.verbose = verbose
# Validate the params
self._validate_init_params()
rand_seed_wrapper()
if self.verbose:
print("Using the following params for GPS model:")
pprint(self.get_params(), indent=4)
def __init__(
self,
treatment_grid_bins,
n_estimators=100,
learning_rate=0.1,
max_depth=5,
random_seed=None,
verbose=False,
):
self.treatment_grid_bins = treatment_grid_bins
self.n_estimators = n_estimators
self.learning_rate = learning_rate
self.max_depth = max_depth
self.random_seed = random_seed
self.verbose = verbose
# Validate the params
self._validate_init_params()
rand_seed_wrapper()
if self.verbose:
print("Using the following params for TMLE model:")
pprint(self.get_params(), indent=4)