statsmodels.robust.norms.estimate_location¶
-
statsmodels.robust.norms.estimate_location(a, scale, norm=
None, axis=0, initial=None, maxiter=30, tol=1e-06)[source]¶ M-estimator of location using self.norm and a current estimator of scale.
This iteratively finds a solution to
norm.psi((a-mu)/scale).sum() == 0
- Parameters:¶
- a : ndarray¶
Array over which the location parameter is to be estimated
- scale : ndarray¶
Scale parameter to be used in M-estimator
- norm : RobustNorm, optional¶
Robust norm used in the M-estimator. The default is HuberT().
- axis : int, optional¶
Axis along which to estimate the location parameter. The default is 0.
- initial : ndarray, optional¶
Initial condition for the location parameter. Default is None, which uses the median of a.
- niter : int, optional
Maximum number of iterations. The default is 30.
- tol : float, optional¶
Toleration for convergence. The default is 1e-06.
- Returns:¶
mu – Estimate of location
- Return type:¶
ndarray