SyntheticControl

class causalpy.pymc_experiments.SyntheticControl

A wrapper around the PrePostFit class

Parameters:

• data (DataFrame) – A pandas dataframe

• treatment_time (Union[int, float, Timestamp]) – The time when treatment occured, should be in reference to the data index

• formula (str) – A statistical model formula

• validation_time – Optional time to split the data into training and validation data sets

• model – A PyMC model

Methods

SyntheticControl.__init__(data, ...[, ...])
SyntheticControl.plot([plot_predictors])	Plot the results
SyntheticControl.print_coefficients([round_to])	Prints the model coefficients
SyntheticControl.summary([round_to])	Print text output summarising the results

Attributes

expt_type
idata	Access to the models InferenceData object
model

__init__(data, treatment_time, formula, validation_time=None, model=None, **kwargs)

Parameters:

• data (DataFrame)

• treatment_time (int | float | Timestamp)

• formula (str)

Return type:

None

__new__(*args, **kwargs)