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={'frac': 0.2, 'it': 0})

Generates data for synthetic control example.

Parameters:

• N – Number of data points

• treatment_time – Index where treatment begins in the generated dataframe

• grw_mu – Mean of Gaussian Random Walk

• grw_sigma – Standard deviation of Gaussian Random Walk

Lowess_kwargs:

Keyword argument dictionary passed to statsmodels lowess

Example

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