statsmodels.robust.scale.Huber
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class statsmodels.robust.scale.Huber(c=1.5, tol=1e-08, maxiter=30, norm=None)
[source] -
Huber?s proposal 2 for estimating location and scale jointly.
Parameters: c : float, optional
Threshold used in threshold for chi=psi**2. Default value is 1.5.
tol : float, optional
Tolerance for convergence. Default value is 1e-08.
maxiter : int, optional0
Maximum number of iterations. Default value is 30.
norm : statsmodels.robust.norms.RobustNorm, optional
A robust norm used in M estimator of location. If None, the location estimator defaults to a one-step fixed point version of the M-estimator using Huber?s T.
call :
Return joint estimates of Huber?s scale and location.
Examples
>>> import numpy as np >>> import statsmodels.api as sm >>> chem_data = np.array([2.20, 2.20, 2.4, 2.4, 2.5, 2.7, 2.8, 2.9, 3.03, ... 3.03, 3.10, 3.37, 3.4, 3.4, 3.4, 3.5, 3.6, 3.7, 3.7, 3.7, 3.7, ... 3.77, 5.28, 28.95]) >>> sm.robust.scale.huber(chem_data) (array(3.2054980819923693), array(0.67365260010478967))
Methods
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