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)