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: [EMAIL PROTECTED] tel: 970 226-9326 sj <[EMAIL PROTECTED]> Sent by: [EMAIL PROTECTED] 10/07/2008 12:38 PM To r-help <[EMAIL PROTECTED]> cc 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 [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.