econml.validate.CalibrationEvaluationResults

class econml.validate.CalibrationEvaluationResults(cal_r_squared: numpy.array, plot_data_dict: Dict[Any, pandas.core.frame.DataFrame], treatments: numpy.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: numpy.array, plot_data_dict: Dict[Any, pandas.core.frame.DataFrame], treatments: numpy.array)[source]

Methods

`__init__`(cal_r_squared, plot_data_dict, ...)
`plot_cal`(tmt)	Plots group average treatment effects (GATEs) and predicted GATEs by quantile-based group in validation sample.
`summary`()	Constructs dataframe summarizing the results of the calibration test.

plot_cal(tmt: Any)[source]

Plots 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() → pandas.core.frame.DataFrame[source]

Constructs dataframe summarizing the results of the calibration test.

Parameters: None
Return type: pandas dataframe containing summary of calibration test results