Returns the value of Jaeckel's dispersion function for given values of the regression coefficents.
disp(beta, x, y, scores)
p by 1 vector of regression coefficents
n by p design matrix
n by 1 response vector
an object of class scores
John Kloke, Joseph McKean
Returns the value of Jaeckel's disperion function evaluated at the value of the parameters in the function call. That is, \(sum_{i=1}^n a(R(e_i)) * e_i\) where R denotes rank and a(1) <= a(2) <= ... <= a(n) are the scores. The residuals (e_i i=1,...n) are calculated y - x beta.
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.
rfit
drop.test
summary.rfit