RobStatTM: rho – R documentation

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rho

Rho functions

Description

This function returns the value of the "rho" loss function used to compute either an M-scale estimator or a robust regression estimator. It currently can be used to compute the bisquare, optimal and modified optimal loss functions.

Usage

rho(u, family = " bisquare", cc, standardize = TRUE)

Arguments

`u`	point or vector at which rho is to be evaluated
`family`	family string specifying the name of the family of loss function to be used (current valid options are "bisquare", "opt" and "mopt").
`cc`	tuning parameters to be computed according to efficiency and / or breakdown considerations. See lmrobdet.control, bisquare, mopt and opt.
`standardize`	logical value determining whether the rho function is to be standardized so that its maximum value is 1. See Mpsi.

Value

The value(s) of rho at u

Author(s)

Matias Salibian-Barrera, matias@stat.ubc.ca

Examples

# Evaluate rho tuned for 85% efficiency
rho(u=1.1, family='bisquare', cc=bisquare(.85))
# Evaluate rho tuned for 50% breakdown
rho(u=1.1, family='opt', cc=lmrobdet.control(bb=.5, family='opt')$tuning.chi)

RobStatTM

Robust Statistics: Theory and Methods

v1.0.2

GPL (>= 3)

Authors

Matias Salibian-Barrera [cre], Victor Yohai [aut], Ricardo Maronna [aut], Doug Martin [aut], Gregory Brownson [aut] (ShinyUI), Kjell Konis [aut], Kjell Konis [cph] (erfi), Christophe Croux [ctb] (WBYlogreg, BYlogreg), Gentiane Haesbroeck [ctb] (WBYlogreg, BYlogreg), Martin Maechler [cph] (lmrob.fit, lmrob..M..fit, lmrob.S), Manuel Koller [cph] (lmrob.fit, .vcov.avar1, lmrob.S, lmrob.lar), Matias Salibian-Barrera [aut]

Initial release

2020-03-02

rho