econml.validate.CalibrationEvaluationResults

class econml.validate.CalibrationEvaluationResults(cal_r_squared: array, plot_data_dict: Dict[Any, DataFrame], treatments: array)[source]

Bases: object

Results class for calibration test.

Parameters:

  • cal_r_squared (list or numpy array of floats) – Sequence of calibration R^2 values

  • plot_data_dict (dict) – Dictionary mapping treatment levels to dataframes containing necessary data for plotting calibration test GATE results

  • treatments (list or numpy array of floats) – Sequence of treatment labels

__init__(cal_r_squared: array, plot_data_dict: Dict[Any, DataFrame], treatments: array)[source]

Methods

__init__(cal_r_squared, plot_data_dict, ...)

plot_cal(tmt)

Plot group average treatment effects (GATEs) and predicted GATEs by quantile-based group in validation sample.

summary()

Construct a dataframe summarizing the results of the calibration test.
plot_cal(tmt: Any)[source]

Plot group average treatment effects (GATEs) and predicted GATEs by quantile-based group in validation sample.

Parameters:

tmt (Any) – Name of treatment to plot

Return type:

matplotlib plot with predicted GATE on x-axis and GATE (and 95% CI) on y-axis

summary() → DataFrame[source]

Construct a dataframe summarizing the results of the calibration test.

Parameters:

None

Return type:

pandas dataframe containing summary of calibration test results