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.
- a
- Returns:¶
- mu
ndarray
Estimate of location
- mu
Last update:
Oct 03, 2024