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...t$fitted.values,nrow=nrow(x),byrow=F),ticktype='detailed', col='lightblue', xlab='x',ylab='y',zlab='z',shade=.75,ltheta=50,main='MARS', phi=25,theta=55,zlim=lims) (the code is also here if someone wants to try it: http://venda.uku.fi/~jmhuttun/R/marstest.R) The results are here: http://venda.uku.fi/~jmhuttun/R/R-10.pdf . The fitted model contains only 5 terms which is not enough in this case. Adjusting parameters like nk, thresh, penalty and degree seems only have minor effect or no effect at all. It's also strange that when I in...

Hi, I'm trying to understand why the coefficients "a" and "b" for the model: W = a*L^b estimated via nls() differs from those obtained for the log transformed model: log(W) = log(a) + b*log(L) estimated via lm(). Also, if I didn't make a mistake, R-squared suggests a "better" adjustment for the model using coefficients estimated by lm() . Perhaps I'm