generate_synthetic_control_data#

causalpy.data.simulate_data.generate_synthetic_control_data(N=100, treatment_time=70, grw_mu=0.25, grw_sigma=1, lowess_kwargs=None)[source]#

Generates data for synthetic control example.

Parameters:

N (int) – Number of data points
treatment_time (int) – Index where treatment begins in the generated dataframe
grw_mu (float) – Mean of Gaussian Random Walk
grw_sigma (float) – Standard deviation of Gaussian Random Walk
lowess_kwargs (dict[str, Any] | None)

Lowess_kwargs:

Keyword argument dictionary passed to statsmodels lowess

Return type:

tuple[DataFrame, ndarray]

Example

>>> from causalpy.data.simulate_data import generate_synthetic_control_data
>>> df, weightings_true = generate_synthetic_control_data(treatment_time=70)