Dear statistics experts, I'm looking for a way to compare the fit of the following three models: LinModel <- lm(y ~ x) LogModel <- nls(y ~ SSlogis(x, Asym, xmid, scal)) PotModel <- nls(y ~ a * x^n, start=list(a=1, n=1)) I am only interested in whether one of these models has substantial advances in explaining the variance of y. So my original idea was simply to compare the adjusted R squared values. This however seems to be problematic for nls models, as I learned from an earlier thread on this issue (see http://article.gmane.org/gmane.comp.lang.r.general/40727). Then I thought about using AIC instead, but again this does not seem to be trivial (see http://article.gmane.org/gmane.comp.lang.r.general/22438). Do you have any suggestions on how I should proceed? Best regards & thanks in advance, Joerg
Spencer Graves
2006-Mar-18 04:01 UTC
[R] How to compare fit of linear and nonlinear models
Your first model "y~x" is a special case of "y~a*x^n", so it should the comparison of those models should be straightforward: Does the confidence inteval for "n" include 1? It is not so easy to compare the second model with either the first or the third. While model 1 is a special case of model 3, we can't get either as a special case of model 2 nor vice versa. For ideas about how to approach this comparison, see my earlier post on a related question (http://finzi.psych.upenn.edu/R/Rhelp02a/archive/35450.html). If it's sufficiently important, it should not be too dificult to Monte Carlo various ways of possibly deciding between the models. hope this helps. spencer graves Joerg Trojan wrote:> Dear statistics experts, > > I'm looking for a way to compare the fit of the following three models: > > LinModel <- lm(y ~ x) > LogModel <- nls(y ~ SSlogis(x, Asym, xmid, scal)) > PotModel <- nls(y ~ a * x^n, start=list(a=1, n=1)) > > I am only interested in whether one of these models has substantial advances in > explaining the variance of y. So my original idea was simply to compare the > adjusted R squared values. This however seems to be problematic for nls models, > as I learned from an earlier thread on this issue (see > http://article.gmane.org/gmane.comp.lang.r.general/40727). > > Then I thought about using AIC instead, but again this does not seem to be > trivial (see http://article.gmane.org/gmane.comp.lang.r.general/22438). > > Do you have any suggestions on how I should proceed? > > > Best regards & thanks in advance, > Joerg > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
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