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