InstrumentalVariableRegression.build_model

InstrumentalVariableRegression.build_model(X, Z, y, t, coords, priors, vs_prior_type=None, vs_hyperparams=None, binary_treatment=False)

Specify model with treatment regression and focal regression data and priors.

Parameters:

• X (np.ndarray) – Array used to predict our outcome y.

• Z (np.ndarray) – Array used to predict our treatment variable t.

• y (np.ndarray) – Array of values representing our focal outcome y.

• t (np.ndarray) – Array representing the treatment t of which we’re interested in estimating the causal impact.

• coords (dict) – Dictionary with the coordinate names for our instruments and covariates.

• priors (dict) – Dictionary of priors for the mus and sigmas of both regressions. Example: priors = {"mus": [0, 0], "sigmas": [1, 1], "eta": 2, "lkj_sd": 2}.

• vs_prior_type (An optional string. Can be "spike_and_slab") – or “horseshoe” or “normal

• vs_hyperparams (An optional dictionary of priors for the) – variable selection hyperparameters

• binary_treatment (A flag for determining the relevant) – likelihood to be used.

Return type:

None