John,
You can make a local version of bootcov which either:
deletes these arguments from the call to fitter, or
modify the switch statement to include rq.fit,
the latter would need to also modify rq() to return a fitFunction
component, so the first option is simpler. One of these days I'll
incorporate clustered se's into summary.rq, but meanwhile
this seems to be a good alternative.
Roger
url: www.econ.uiuc.edu/~roger Roger Koenker
email rkoen...@uiuc.edu Department of Economics
vox: 217-333-4558 University of Illinois
fax: 217-244-6678 Urbana, IL 61801
On Jul 23, 2009, at 8:10 PM, John Gardner wrote:
I have a quick question, and I apologize in advance if, in asking, I
expose my woeful ignorance of R and its packages. I am trying to use
the bootcov function to estimate the standard errors for some
regression quantiles using a cluster bootstrap. However, it seems that
bootcov passes arguments that rq.fit doesn't like, preventing the
command from executing. Here is an example:
e<-bootcov(rq(y~x),clust,B=10,fitter=rq.fit)
(where clust is my clustering variable) results in
Error in rq.fit.br(x, y, tau = tau, ...) :
unused argument(s) (maxit = 15, penalty.matrix = NULL)
In contrast, the lm.fit function seems to just ignore these arguments,
resulting in the following warning:
10: In fitter(X[obs, , drop = FALSE], Y[obs, , drop = FALSE], maxit
= maxit, :
extra arguments maxitpenalty.matrix are just disregarded.
Is there a way that I can either (a) modify bootcov so that it doesn't
pass these arguments or (b) modify rq so that it ignores them?
Thanks in advance,
John Gardner
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