On Fri, 24 Jun 2005, james lumley wrote: > Hi, I'm looking to implement a regression with mixed terms. I have 2
What do you mean by `mixed'? Not I think in the sense of Pinheiro & Bates' book or nlme. > biological endpoints for a dataset of n=77, one linearly related and > the other fits a spline. I want to combine these two terms in a > linear regression for prediction, then apply the model to a test set. > > this works fine, good r2 and I've graphed the spline. > m1<-lm(y~x1,data=train) > m2<-smooth.spline(x2,y); (spl) > > what i want is > y=x+bilin(x2) You can see several ways to do this in MASS. Most simply lm(y ~ x1 + ns(s2, df=?)) for regression splines. For smoothing splines, see the functions gam() in packages mgcv and gam (which differ considerably), or bruto() in mda or package gss or .... -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [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
