statsmodels.robust.norms.RamsayE

class statsmodels.robust.norms.RamsayE(a=0.3)

Ramsay’s Ea for M estimation

Parameters:

afloat, optional

The tuning constant for Ramsay’s Ea function. It has to be positive. The default value is 0.3.

Methods

__call__(z)

Return the value of estimator rho applied to an input

Raises:

TypeError

If a is not a real number.

ValueError

If a is not positive, or is nan.

See also

statsmodels.robust.norms.RobustNorm

Notes

Changed in version 0.15.1: The tuning constant is validated. Zero, negative and nan values raise a ValueError instead of creating a degenerate norm.

The tuning constant is validated when the norm is created and in _set_tuning_param. Plain attribute assignment after construction, norm.a = value, is not validated.

Methods

max_rho()
psi(z)	The psi function for Ramsay's Ea estimator
psi_deriv(z)	The derivative of Ramsay's Ea psi function
rho(z)	The robust criterion function for Ramsay's Ea
weights(z)	Ramsay's Ea weighting function for the IRLS algorithm

Properties

continuous
redescending