good usually means good relative to something else, in this case the comparison seems, as Michael has already said, f0 <- rq(y ~ 1, tau = ?) and then one can compute the R1 version that I originally suggested. But since there is still no explicit way to evaluate this, it is all a bit pointless.
Roger Koenker rkoen...@illinois.edu On Apr 24, 2013, at 6:37 PM, R. Michael Weylandt wrote: >> On Tue, Apr 23, 2013 at 2:54 PM, nafiseh hagiaghamohammadi >> <n_hajiaghamohammadi2...@yahoo.com> wrote: >>> Hi >>> >>> I fit one linear quantile regression with package quantreg and I want to >>> khow this model is good or not.Is there method for checking it? >>> Thanks your advice > >> I ask this question because there is 2 models,f0 and f1 in (R1 <- 1 - >> f1$rho/f0$rho ), >> is it true? >> >> but I fit 1 model and I want to check goodness of fit for 1 model . >> >> > > Please keep your responses on list so you can get a quick reply even > when I'm otherwise busy. > > I think you could -- for a rough and ready comparison -- compare > against a constant (empirical quantile) model (not unlike how basic > OLS models compare against the constant mean predictor) but someone > else might know if there's any subtleties about quantile regression > that should be noted here. > > MW > > ______________________________________________ > 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. ______________________________________________ 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.
