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...of appropriate predictors. Thanks Savrina *mgcv package 1.3-12: # I start with specifying the full model with 116 predictors including isotropic smooth of 3D location variables (when I specify only the first 14 predictors I get no error message) > m0<-gam(label~s(x,y,z,k=50),s+(feature4)+s(feature5)+s(feature6)+...+s(feature116),data=k.data, family=binomial) Error in smooth.construct.tp.smooth.spec(object, data, knots): A term has fewer unique covariate combinations than specified maximum degrees of freedom # I was going to follow this with backwards selection by hypothesis testing (re...