.BG
.FN rbiwt
.TL
Robust Simple Regression by Biweight
.CS
rbiwt(x, y, start, k=6, tol=.001, iter=20)
.AG x
vector of observations on independent variable.
.AG y
vector of observations on dependent variable.
.AG start
vector giving starting values of intercept and slope.
Default, use least-squares start.
.AG k
biweight scale parameter.
.AG tol
convergence criterion.
.AG iter
maximum number of iterations.
.RT
list containing components `coef', `resid', and `wt'.
.RC coef
vector giving intercept and slope.
.RC resid
vector like `y' giving residuals from fit.
.RC wt
vector giving weights used in final weighted least-squares
step.
.SH REFERENCE
Coleman, D., Holland, P., Kaden, N., Klema, V., and Peters, S. C.,
"A System of Subroutines for Iteratively Re-Weighted Least-Squares Computations",
.ul
ACM Trans. Math. Soft.,
Vol. 6, pp. 327-336, 1980.
.SA
Function `rreg' generalizes `rbiwt' to multiple regression.
.EX
plot(x,y)
abline(rbiwt(x,y))     #add line to plot
.KW array
.KW regression
.KW robust
.WR
