GradedInterventionTimeSeries.__init__#
- GradedInterventionTimeSeries.__init__(data, y_column, treatment_names, base_formula, model=None, **kwargs)[source]#
Initialize experiment with data and unfitted model (standard CausalPy pattern).
This method: 1. Validates inputs and builds baseline design matrix 2. Estimates transform parameters for each treatment 3. Applies transforms and builds full design matrix 4. Calls model.fit(X_full, y) 5. Extracts results for visualization and analysis
- Parameters:
data (pd.DataFrame) – Time series data.
y_column (str) – Name of outcome variable.
treatment_names (List[str]) – List of treatment variable names (e.g., [“comm_intensity”]).
base_formula (str) – Patsy formula for baseline model.
model (TransferFunctionOLS) – UNFITTED model with configuration for transform estimation.