I am trying to compute the white heteroskedasticity-robust standard errors (also called the Huber standard errors) in a linear model, but I can't seem to find a function to do it. I know that the design library in S+ has something like this (robcov?), but I have not yet seen this library ported to R. Anyone know if there is already a function built into R to do this relatively simple job? Thanks, Grant ------------------------------------------------------ Grant Verdell Farnsworth gvf at email.byu.edu http://thegrantman.freewebsites.com ------------------------------------------------------ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Hi, I attach a version of small program for White stderrors. Basically, it calculates a new covariance matrix and prints the results with new stderrors (without any tests and additional information). It should be rewritten to use the object-oriented architecture, but I have not had need so long. you should call it as: summaryw(lm(y~x)) Regards, Ott Toomet P.S. If you get/write a better version, let me know. -------------------------------------------------------------------- ### ols with White' heteroscedasticity consistent stderrors summaryw <- function( model) { s <- summary( model) X <- model.matrix( model) u2 <- residuals( model)^2 XDX <- 0 ## here one needs essentially to calculate X'DX. But due to the fact that D ## is huge (NxN), it is better to do it with a cycle. for( i in 1:nrow( X)) { XDX <- XDX + u2[i]*X[i,]%*%t( X[i,]) } XX1 <- solve( t( X)%*%X) varcovar <- XX1 %*% XDX %*% XX1 stdh <- sqrt( diag( varcovar)) t <- model$coefficients/stdh p <- 2*pnorm( -abs( t)) results <- cbind( model$coefficients, stdh, t, p) dimnames(results) <- dimnames( s$coefficients) results } On Thu, 21 Mar 2002, Grant Farnsworth wrote: |I am trying to compute the white heteroskedasticity-robust standard errors |(also called the Huber standard errors) in a linear model, but I can't seem |to find a function to do it. I know that the design library in S+ has |something like this (robcov?), but I have not yet seen this library ported |to R. | |Anyone know if there is already a function built into R to do this |relatively simple job? | |Thanks, |Grant -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Try the function hccm in the car package. David ----- Original Message ----- From: "Grant Farnsworth" <gvf at email.byu.edu> To: "rhelp" <r-help at stat.math.ethz.ch> Sent: Friday, March 22, 2002 2:09 AM Subject: [R] heteroskedasticity-robust standard errors> I am trying to compute the white heteroskedasticity-robust standard errors > (also called the Huber standard errors) in a linear model, but I can'tseem> to find a function to do it. I know that the design library in S+ has > something like this (robcov?), but I have not yet seen this library ported > to R. > > Anyone know if there is already a function built into R to do this > relatively simple job? > > Thanks, > Grant > > ------------------------------------------------------ > Grant Verdell Farnsworth > gvf at email.byu.edu > http://thegrantman.freewebsites.com > ------------------------------------------------------ > > > -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-> r-help mailing list -- Readhttp://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html> Send "info", "help", or "[un]subscribe" > (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch >_._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._. _._> >-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Grant Farnsworth wrote:> > I am trying to compute the white heteroskedasticity-robust standard errors > (also called the Huber standard errors) in a linear model, but I can't seem > to find a function to do it. I know that the design library in S+ has > something like this (robcov?), but I have not yet seen this library ported > to R. > > Anyone know if there is already a function built into R to do this > relatively simple job?There are some version of heteroskedasticity consistent covariance matrices in the "car" package in hccm() and in "strucchange" in covHC(). In particular both contain the White (1980) estimator as type "hc0" and "HC" respectively. Z> Thanks, > Grant > > ------------------------------------------------------ > Grant Verdell Farnsworth > gvf at email.byu.edu > http://thegrantman.freewebsites.com > ------------------------------------------------------ > > -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- > r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html > Send "info", "help", or "[un]subscribe" > (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch > _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._