linearmodels.iv.model.IVGMMCUE.estimate_parameters¶

IVGMMCUE.estimate_parameters(starting: ndarray[tuple[int, ...], dtype[float64]], x: ndarray[tuple[int, ...], dtype[float64]], y: ndarray[tuple[int, ...], dtype[float64]], z: ndarray[tuple[int, ...], dtype[float64]], display: bool = False, opt_options: dict[str, Any] | None = None) → tuple[ndarray[tuple[int, ...], dtype[float64]], int][source]¶

Parameters:¶

starting: ndarray[tuple[int, ...], dtype[float64]]¶: Starting values for the optimization
x: ndarray[tuple[int, ...], dtype[float64]]¶: Regressor matrix (nobs by nvar)
y: ndarray[tuple[int, ...], dtype[float64]]¶: Regressand matrix (nobs by 1)
z: ndarray[tuple[int, ...], dtype[float64]]¶: Instrument matrix (nobs by ninstr)
display: bool = False¶: Flag indicating whether to display iterative optimizer output
opt_options: dict[str, Any] | None = None¶: Dictionary containing additional keyword arguments to pass to scipy.optimize.minimize.

Returns:¶

Estimated parameters (nvar by 1)

Return type:¶

numpy.ndarray

Notes

Exposed to facilitate estimation with other data, e.g., bootstrapped samples. Performs no error checking.