### Navigation

- index
- modules |
- next |
- previous |
- statsmodels v0.2.0 documentation »
- Robust Linear Models »

# scikits.statsmodels.robust.norms.estimate_location

`scikits.statsmodels.robust.norms.``estimate_location`(a, scale, norm=<scikits.statsmodels.robust.norms.HuberT object at 0x03305CB0>, axis=0, initial=None, maxiter=30, tol=9.9999999999999995e-007)

  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

### Navigation

- index
- modules |
- next |
- previous |
- statsmodels v0.2.0 documentation »
- Robust Linear Models »