jaeckel: Function to Minimize Jaeckel's Dispersion Function

In kloke/Rfit: Rank-Based Estimation for Linear Models

Function to Minimize Jaeckel's Dispersion Function

Description

Uses the built-in function optim to minimize Jaeckel's dispersion function.

Usage

jaeckel(x, y, beta0 = lm(y ~ x)$coef[2:(ncol(x) + 1)], 
  scores = Rfit::wscores, control = NULL,...)

Arguments

x	n by p design matrix
y	n by 1 response vector
beta0	intial estimate
scores	object of class 'scores'
control	control passed to fitting routine
...	addtional arguments to be passed to fitting routine

Details

Function uses optim with method set to BFGS to minimize Jaeckel's dispersion function. If control is not specified at the function call, the relative tolerance (reltol) is set to .Machine$double.eps^(3/4) maximum number of iterations is set to 200. See optim.

Value

Results of optim are returned.

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.

Kapenga, J. A., McKean, J. W., and Vidmar, T. J. (1988), RGLM: Users Manual, Statist. Assoc. Short Course on Robust Statistical Procedures for the Analysis of Linear and Nonlinear Models, New Orleans.

See Also

optim, rfit

Examples

##  This is a internal function.  See rfit for user-level examples.

kloke/Rfit documentation built on Sept. 9, 2023, 7:20 p.m.