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:¶
Notes
Exposed to facilitate estimation with other data, e.g., bootstrapped samples. Performs no error checking.
See also