There are possibilities with rqss() as someone else mentioned. But you can also conduct a lot of useful modeling just by using b-splines within the the rq function - something like my.result <- rq(y ~ bs(x,degree=3)), where bs() is the b-spline function from the splines package. You get to specifiy the degree of polynomial and number and location of knots.
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 From: Jonathan Greenberg <[email protected]> To: "[email protected]" <[email protected]> Date: 05/29/2009 05:55 PM Subject: [R] Quantile GAM? Sent by: [email protected] R-ers: I was wondering if anyone had suggestions on how to implement a GAM in a quantile fashion? I'm trying to derive a model of a "hull" of points which are likely to require higher-order polynomial fitting (e.g. splines)-- would quantreg be sufficient, if the response and predictors are all continuous? Thanks! --j ______________________________________________ [email protected] 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]] ______________________________________________ [email protected] 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.
