R: Robust Location-Free Scale Estimate More Efficient than MAD

Sn {robustbase} | R Documentation

## Robust Location-Free Scale Estimate More Efficient than MAD

### Description

Compute the robust scale estimator Sn, an efficient alternative to the MAD.

### Usage

    Sn(x, constant = 1.1926, finite.corr = missing(constant))

    s_Sn(x, mu.too = FALSE, ...)

### Arguments

`x` | numeric vector of observations.
`constant` | number by which the result is multiplied; the default achieves consisteny for normally distributed data.
`finite.corr` | logical indicating if the finite sample bias correction factor should be applied. Default to `TRUE` unless `constant` is specified.
`mu.too` | logical indicating if the `median(x)` should also be returned for `s_Sn()`.
`...` | potentially further arguments for `s_Sn()` passed to `Sn()`.

### Details

............ FIXME ........

### Value

`Sn()` returns a number, the Sn robust scale estimator, scaled to be consistent for σ^2 and i.i.d. Gaussian observatsions, optionally bias corrected for finite samples.

`s_Sn(x, mu.too=TRUE)` returns a length-2 vector with location (μ) and scale; this is typically only useful for `covOGK(*, sigmamu = s_Sn)`.

### Author(s)

Original Fortran code: Christophe Croux and Peter Rousseeuw rousse@wins.uia.ac.be.
Port to C and R: Martin Maechler, maechler@R-project.org

### References

Rousseeuw, P.J. and Croux, C. (1993) Alternatives to the Median Absolute Deviation, Journal of the American Statistical Association 88, 1273–1283.

### See Also

`mad` for the ‘most robust’ but much less efficient scale estimator; `Qn` for a similar more efficient but slower alternative; `scaleTau2`.

### Examples

    x <- c(1:10, 100+1:9)# 9 outliers out of 19
    Sn(x)
    Sn(x, c=1)# 9
    Sn(x[1:18], c=1)# 9
    set.seed(153)
    x <- sort(c(rnorm(80), rt(20, df = 1)))
    s_Sn(x, mu.too=TRUE)

[Package robustbase version 0.93-6 Index]