statsmodels.robust.norms.StudentT

class statsmodels.robust.norms.StudentT(c=2.3849, df=4)

Robust norm based on t distribution

Rho is a rescaled version of the t-loglikelihood function after dropping constant terms. The norms are rescaled so that the largest weights are 1 and the second derivative of the rho function at zero is equal to 1.

The maximum likelihood estimator based on the loglikelihood function of the t-distribution is available in statsmodels.miscmodels, which can be used to also estimate scale and degrees of freedom by MLE.

Parameters:

cfloat, optional

The tuning constant for the StudentT norm. The default value is 2.3849.

dffloat, optional

The degrees of freedom of the t distribution used to derive the norm. The default value is 4.

Methods

__call__(z)	Return the value of estimator rho applied to an input
psi(z)	The psi function of the StudentT norm
psi_deriv(z)	The derivative of the psi function of the StudentT norm
rho(z)	The rho function of the StudentT norm
weights(z)	The weighting function for the IRLS algorithm of the StudentT norm

max_rho

Methods

max_rho()
psi(z)	The psi function of the StudentT norm
psi_deriv(z)	The derivative of the psi function of the StudentT norm
rho(z)	The rho function of the StudentT norm
weights(z)	The weighting function for the IRLS algorithm of the StudentT norm

Properties

continuous
redescending