giant.calibration.estimators.geometric.lmaΒΆ
Classes
LMAEstimatorOptions(weighted_estimation: bool = False, a_priori_model_covariance: Optional[numpy.ndarray[tuple[Any, ...], numpy.dtype[numpy.float64]]] = None, max_iter: int = 20, residual_atol: float = 1e-10, residual_rtol: float = 1e-10, state_atol: float = 1e-10, state_rtol: float = 1e-10, max_divergence_steps: int = 5) |
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This implements a Levenberg-Marquardt Algorithm estimator, which is analogous to a damped iterative non-linear least squares. |
