grad {Rfit}R Documentation

Calculate the Gradiant of Jaeckel's Dispersion Function

Description

Calculate the Gradiant of Jaeckel's Dispersion Function

Usage

grad(x, y, beta, scores)

Arguments

x

n by p design matrix

y

n by 1 response vector

beta

p by 1 vector of regression coefficients

scores

an object of class scores

Value

The gradiant evaluated at beta.

Author(s)

John Kloke

References

Hettmansperger, T.P. and McKean J.W. (2011), Robust Nonparametric Statistical Methods, 2nd ed., New York: Chapman-Hall.

Jaeckel, L. A. (1972). Estimating regression coefficients by minimizing the dispersion of residuals. Annals of Mathematical Statistics, 43, 1449 - 1458.

Jureckova, J. (1971). Nonparametric estimate of regression coefficients. Annals of Mathematical Statistics, 42, 1328 - 1338.

See Also

disp

Examples

## The function is currently defined as
function (x, y, beta, scores) 
{
    x <- as.matrix(x)
    e <- y - x %*% beta
    r <- rank(e, ties.method = "first")/(length(e) + 1)
    -t(x) %*% scores@phi(r)
  }

[Package Rfit version 0.27.0 Index]