Skip to content
/ FRB Public
forked from msalibian/FRB

Fast and robust bootstrap for robust regression estimators

License

Notifications You must be signed in to change notification settings

guhjy/FRB

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

18 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

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

About

Fast and robust bootstrap for robust regression estimators

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • C 78.9%
  • R 21.1%