tukeyPsi1 {robustbase} | R Documentation

## Tukey's Bi-square Score (Psi) and "Chi" (Rho) Functions and Derivatives

### Description

These are deprecated, replaced by `Mchi(*, psi="tukey")`, `Mpsi(*, psi="tukey")`

`tukeyPsi1()` computes Tukey's bi-square score (psi) function, its first derivative or it's integral/“principal function”. This is scaled such that ψ'(0) = 1, i.e., psi(x) ~= x around 0.

`tukeyChi()` computes Tukey's bi-square loss function, `chi(x)` and its first two derivatives. Note that in the general context of M-estimators, these loss functions are called rho-functions.

### Usage

    tukeyPsi1(x, cc, deriv = 0)
    tukeyChi (x, cc, deriv = 0)

### Arguments

`x` | numeric vector.
`cc` | tuning constant
`deriv` | integer in \{-1,0,1,2\} specifying the order of the derivative; the default, `deriv = 0` computes the psi-, or chi- ("rho"-)function.

### Value

a numeric vector of the same length as `x`.

### Note

`tukeyPsi1(x, d)` and `tukeyChi(x, d+1)` are just re-scaled versions of each other (for `d in -1:1`), i.e.,

χ^{(ν)}(x, c) = (6/c^2) ψ^{(ν-1)}(x,c),

for ν = 0,1,2.

We use the name ‘tukeyPsi1’, because `tukeyPsi` is reserved for a future “Psi Function” class object, see `psiFunc`.

### Author(s)

Matias Salibian-Barrera, Martin Maechler and Andreas Ruckstuhl

### See Also

`lmrob` and `Mpsi`; further `anova.lmrob` which needs the `deriv = -1`.

### Examples

    op <- par(mfrow = c(3,1), oma = c(0,0, 2, 0),
              mgp = c(1.5, 0.6, 0), mar= .1+c(3,4,3,2))
    x <- seq(-2.5, 2.5, length = 201)
    cc <- 1.55 # as set by default in lmrob.control()
    plot. <- function(...) { plot(...); abline(h=0,v=0, col="gray", lty=3)}
    plot.(x, tukeyChi(x, cc), type = "l", col = 2)
    plot.(x, tukeyChi(x, cc, deriv = 1), type = "l", col = 2)
    plot.(x, tukeyChi(x, cc, deriv = 2), type = "l", col = 2)

    mtext(sprintf("tukeyChi(x, c = %g, deriv),  deriv = 0,1,2", cc),
          outer = TRUE, font = par("font.main"), cex = par("cex.main"))
    par(op)

    op <- par(mfrow = c(3,1), oma = c(0,0, 2, 0),
              mgp = c(1.5, 0.6, 0), mar= .1+c(3,4,1,1))
    x <- seq(-5, 5, length = 201)
    cc <- 4.69 # as set by default in lmrob.control()
    plot. <- function(...) { plot(..., asp = 1); abline(h=0,v=0, col="gray", lty=3)}
    plot.(x, tukeyPsi1(x, cc), type = "l", col = 2)
    abline(0:1, lty = 3, col = "light blue")
    plot.(x, tukeyPsi1(x, cc, deriv = -1), type = "l", col = 2)
    plot.(x, tukeyPsi1(x, cc, deriv =  1), type = "l", col = 2); abline(h=1,lty=3)

    mtext(sprintf("tukeyPsi1(x, c = %g, deriv),  deriv = 0, -1, 1", cc),
          outer = TRUE, font = par("font.main"), cex = par("cex.main"))
    par(op)

[Package robustbase version 0.93-4 Index]