A possiblie solution might be to use the survey package. You could specify
that the data is clustered using the svydesign function, and then speciy the
replicate weights using the as.svrepdesign function. And then, it would be
possible to use the withReplicates function to bootstrap the clusters
A piece of this is solved by the rms package's Rq and bootcov functions.
-Frank
Roger Koenker-3 wrote
> There is no automatic "clustering" option for QR bootstrapping.
> You will have to roll your own.
>
>
> url:www.econ.uiuc.edu/~rogerRoger Koenker
> email
> rkoenker@
>
There is no automatic "clustering" option for QR bootstrapping.
You will have to roll your own.
url:www.econ.uiuc.edu/~rogerRoger Koenker
emailrkoen...@uiuc.eduDepartment of Economics
vox: 217-333-4558University of Illinois
fax: 217-244-66
sry, I forgot to replace rlm() - but actually I tried both and the question
applies to both approaches..
Am 31.10.2012 00:19 schrieb "Kay Cichini" :
>
> HI everyone,
>
> I try to get some bootstrap CIs for coefficients obtained by quantile
regression. I have influencial values and thus switched to
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