Try the linear quantile regression function rq() in the quantreg package. 
For 1 sample estimates, your model would have just an intercept term. 
There is a weight argument.

quantiles.out <- rq(y ~ 1, data=mydata, tau=1:9/10, weight=myweights)

would yield the 0.10, 0.20, ..., 0.80, 0.90 weighted quantile estimates.

Brian

Brian S. Cade, PhD

U. S. Geological Survey
Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO  80526-8818

email:  brian_cade@usgs.gov
tel:  970 226-9326



sj <ssj1364@gmail.com> 
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10/07/2008 12:38 PM

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Subject
[R] weighted quantiles






I have a set of values and their corresponding weights. I can use the
function weighted.mean to calculate the weighted mean, I would like to be
able to similarly calculate the weighted median and quantiles? Is there a
function in R that can do this?

thanks,


Spencer

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