statsmodels.robust.norms.estimate_location

statsmodels.robust.norms.estimate_location(a, scale, norm=None, axis=0, initial=None, maxiter=30, tol=1e-06)

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 : array

Array over which the location parameter is to be estimated

scale : array

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 : array, 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 : array

Estimate of location