Please see the posting guide and provide a reproducible example.
If this is package 'gam', prediction difficulties of this sort for the S version are discussed in the White Book, MASS and elsewhere (but I recall reading that they did not apply to the R version).
On Wed, 23 Mar 2005, Kerry Bush wrote:
Recently I was using GAM and couldn't help noticing the following incoherence in prediction:
data(gam.data) data(gam.newdata)
It is unusual to use data() on your own objects, but we cannot reproduce what you did without data.
gam.object <- gam(y ~ s(x,6) + z, data=gam.data) predict(gam.object)[1]1 0.8017407
predict(gam.object,data.frame(x=gam.data$x[1],z=gam.data$z[1])) 1 0.1668452
I would expect that using two types of predict arguments should give me the same results. When I used this to predict a new data set then it seems OK:
predict(gam.object,data.frame(x=gam.newdata$x[1],z=gam.newdata$z[1])) 1 0.4832136predict(gam.object,gam.newdata)[1]1 0.4832136
Could anybody explain the strange behavior of predict.gam function?
-- 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
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