Fit a Robust Linear Model
Fits a robust linear model with high breakdown point and high efficiency estimates. This is used by lmRob, but not supposed to be called by the users directly.
lmRob.fit.compute(x, y, x1.idx = NULL, nrep = NULL, robust.control = NULL, ...)
x |
a numeric matrix containing the design matrix. |
y |
a numeric vector containing the linear model response. |
x1.idx |
a numeric vector containing the indices of columns of the design matrix arising from the coding of factor variables. |
nrep |
the number of random subsamples to be drawn. If |
robust.control |
a list of control parameters to be used in the numerical algorithms. See |
... |
additional arguments. |
an object of class "lmRob". See lmRob.object for a complete description of the object returned.
Gervini, D., and Yohai, V. J. (1999). A class of robust and fully efficient regression estimates, mimeo, Universidad de Buenos Aires.
Marazzi, A. (1993). Algorithms, routines, and S functions for robust statistics. Wadsworth & Brooks/Cole, Pacific Grove, CA.
Maronna, R. A., and Yohai, V. J. (1999). Robust regression with both continuous and categorical predictors, mimeo, Universidad de Buenos Aires.
Yohai, V. (1988). High breakdown-point and high efficiency estimates for regression, Annals of Statistics, 15, 642-665.
Yohai, V., Stahel, W. A., and Zamar, R. H. (1991). A procedure for robust estimation and inference in linear regression, in Stahel, W. A. and Weisberg, S. W., Eds., Directions in robust statistics and diagnostics, Part II. Springer-Verlag.
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