RobStatTM (version 1.0.1)

locScaleM: Robust univariate location and scale M-estimators

Description

This function computes M-estimators for location and scale.

Usage

locScaleM(x, psi = "bisquare", eff = 0.9, maxit = 50, tol = 1e-04)

Arguments

x

a vector of univariate observations

psi

a string indicating which score function to use. Valid options are "bisquare", "huber", "optimal" and "modopt".

eff

desired asymptotic efficiency. Valid options are 0.85, 0.9 (default) and 0.95 when psi = "bisquare" or "huber", and 0.85, 0.9 (default), 0.95 and 0.99 when psi = "optimal" or "modopt".

maxit

maximum number of iterations allowed.

tol

tolerance to decide convergence of the iterative algorithm.

Value

A list with the following components:

mu

The location estimate

std.mu

Estimated standard deviation of the location estimator mu

disper

M-scale/dispersion estimate

Details

This function computes M-estimators for location and scale.

References

http://www.wiley.com/go/maronna/robust

Examples

# NOT RUN {
set.seed(123)
r <- rnorm(150, sd=1.5)
locScaleM(r)
# 10% of outliers, sd of good points is 1.5
set.seed(123)
r2 <- c(rnorm(135, sd=1.5), rnorm(15, mean=-10, sd=.5))
locScaleM(r2)

# }