| Library: | robtech |
| See also: | l1fit lts mve |
| Quantlet: | rdl1 | |
| Description: | Computes RDL1 estimate --- a weighted L1-estimator of y on on continuous variables x and binary variables xdum with weights min(1, p/(RD^2)); RD contains the robust distances obtained by the MVE estimator for x. |
| Usage: | z = rdl1(x,xdum,y) | |
| Input: | ||
| x | n x p1 matrix of continuous explanatory variables. | |
| xdum | n x p2 matrix of binary explanatory variables (including intercept if required). | |
| y | n x 1 vector, dependent variable. | |
| Output: | ||
| z.coefs | (p1+p2) x 1 vector of the estimated regression parameters. | |
| z.weight | n x 1 vector of the robust weights used in L1 regression. | |
| z.res | n x 1 vector of the regression residuals. | |
| z.scale | a robust estimate of scale (median absolute deviation). | |
| z.stres | n x 1 vector of the standardized regression residuals. | |
library("robtech")
randomize(101)
n = 100
x = normal(n)
xdum = matrix(n)~rint(uniform(n))
y = 5 + 2*x - xdum[,2] + normal(n)
; compute the estimate
z = rdl1(x, xdum, y)
z.coefs
Contents of coefs - estimates of b = (2,5,-1)' coefficient vector (coefficient 2 corresponds to the only continuous variable x, coefficients 5 and -1 to the binary variables - intercept and xdum) [1,] 2.2634 [2,] 5.0839 [3,] -0.9755