Hi All, I am using the package quantreg to create a 'model' that I can then use to predict the response variable (volume) from a larger set of explanatory variables (environmental factors):
ie- #model- >fit <- rqss(volume~qss(env.factor1,lambda=1)+ qss(env.factor2,lambda=1), tau = 0.9) >summary(fit) predict volume from new environmental factors for a larger area where I do not know the volume > predi<-predict(fit, new, interval = "none", level = 0.9) However I am getting the following error message: >Error in predict.qss1(qss, newdata = newd, ...) : >no extrapolation allowed in predict.qss Is there a way around this? and also with the initial model, is there a way to test goodness of fit? If so how? because #summary(fit) only tells me if the model is significant not how good it is (like with a linear regression you get and R square value which tells you how good the model is). Thank you All help is appreciated, If you would like anything clarified please contact me, Kitty [[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.