statsmodels.robust.norms.estimate_location
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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 : 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
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