I thought the documentation you quoted is rather clear. The GAM is something like:
g(Y) = sum f_j(x_j) so predict.gam() returns sum f_j(x_j) by default, and if type="response", g^-1(sum f_j(x_j)). This is similar to predict.glm, I believe. HTH, Andy > From: Jon Egil Strand > > > ----------------- > Mac OS X 10.3 > R 2.0.1 > gam 0.9.2 > ----------------- > > Greetings > > I am facing difficulties in prediction on using Trevor > Hasties GAM package. > > How can one interpret the response from predict.gam? > > Documentation on the type-parameter: > The default (link) produces predictions on the scale of the > additive > predictors, ... > > If "response" is selected, the predictions are on the scale of the > response, and are monotone trans-formations of the additive > predictors, > using the inverse link function. > > Does "on the scale of the response" ammount to residals? > > All I want to do is get the predicted response from running > my GAM model > on new data. The results given are way off, but I am not able > to dechipher > the documentation, nor use any scale information. > > > Any help will be highly appreciated. > > > All the best > > Jon Egil Strand > > > > > -- > > Jon Egil Strand > [EMAIL PROTECTED] > Phone: +47 45030081 > > ______________________________________________ > [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 > > ______________________________________________ [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
