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Fast and robust bootstrap for robust regression estimators

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Fast and Robust Bootstrap

Matias Salibian 2016-07-30

Fast and Robust Bootstrap

This package implements the Fast and Robust Bootstrap as proposed in Salibian-Barrera and Zamar (2002), and Salibian-Barrera, M., Van Aels, S. and Willems, G. (2008) for robust regression estimators (MM-estimators) computed with robustbase::lmrob.

To install it use the following commands (assuming that you have the devtools package from CRAN already installed):

library(devtools)
install_github("msalibian/FRB")

To use it (after installation), simply call frb on an lmrob object as computed by robustbase::lmrob. Here's an example:

library(robustbase)
library(FRB)
a <- lmrob(LNOx ~ LNOxEm + sqrtWS, data=NOxEmissions)
set.seed(123)
tmp <- frb(lmrob.object=a, nboot=1000, return.coef=FALSE)

If the argument return.coef is set to FALSE, then frb returns the estimated covariance matrix of the robust regression estimators. For example, the estimated standard errors for each parameter estimate are

sqrt(diag(tmp))
## [1] 0.054340731 0.007633753 0.013364467

We can compare them with the estimated standard errors given by the usual asyptotic approximation:

sqrt(diag(summary(a)$cov))
## (Intercept)      LNOxEm      sqrtWS 
## 0.054256788 0.007482346 0.013222502

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