dualbounds.dist_reg.BinaryDistReg.fit¶

BinaryDistReg.fit(W: array, X: array, y: array, Z: array | None = None, sample_weight: array | None = None) → None[source]¶

Fits model on the data.

Parameters:¶

W : np.array¶

n-length array of binary treatment indicators.

X : np.array¶

(n, p)-shaped array of covariates.

y : np.array¶

n-length array of outcome measurements.

Z : np.array¶

Optional n-length array of instrument values for the instrumental variables setting.

sample_weight : np.array¶

Optional n-length array of weights to use when fitting the underlying model.

Notes

Not all model_types can be trained using sample_weight. For some models (e.g. KNNRegressors), including sample_weight will yield an error.