robustbase (version 0.9-8)

scaleTau2: Robust Tau-Estimate of Scale

Description

Computes the robust $\tau$-estimate of univariate scale, as proposed by Maronna and Zamar (2002); improved by a consistency factor.

Usage

scaleTau2(x, c1 = 4.5, c2 = 3.0, consistency = TRUE,
          mu.too = FALSE, ...)

Arguments

x

numeric vector

c1,c2

non-negative numbers, specifying cutoff values for the biweighting of the mean and the rho function respectively.

mu.too

logical indicating if both location and scale should be returned or just the scale (when mu.too=FALSE as by default).

consistency

logical indicating if the consistency correction factor (for the scale) should be applied.

...

potentially additional arguments which are not used.

Value

• numeric vector of length one (if mu.too is FALSE as by default) or two (when mu.too = TRUE) with robust scale or (location,scale) estimators $\hat\sigma(x)$ or $(\hat\mu(x),\hat\sigma(x))$.

Details

First, $s_0$ := MAD, i.e. the equivalent of mad(x, constant=1) is computed. Robustness weights $w_i := w_{c1}((x_i - med(X))/ s_0)$ are computed, where $w_c(u) = max(0, (1 - (u/c)^2)^2)$. The robust location measure is defined as $\mu(X) := (\sum_i w_i x_i)/(\sum_i w_i)$, and the robust $\tau (tau)$-estimate is $s(X)^2 := s_0^2 * (1/n) \sum_i \rho_{c2}((x_i - \mu(X))/s_0)$, where $\rho_c(u) = min(c^2, u^2)$. scaleTau2(*, consistency=FALSE) returns $s(X)$, whereas this value is divided by its asymptotic limit when consistency = TRUE as by default.

Note that for n = length(x) == 2, all equivariant scale estimates are proportional, and specifically, scaleTau2(x, consistency=FALSE) == mad(x, constant=1). See also the reference.

References

Maronna, R.A. and Zamar, R.H. (2002) Robust estimates of location and dispersion of high-dimensional datasets; Technometrics 44(4), 307--317.

See Also

Sn, Qn, mad; further covOGK for which scaleTau2 was designed.

Examples

x <- c(1:7, 1000)
sd(x) # non-robust std.deviation
scaleTau2(x)
scaleTau2(x, mu.too = TRUE)