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
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]