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1. question on nls (score: 1): Author: "Tropmedres" <pan@tropmedres.ac>; Date: Wed, 3 Mar 2004 17:31:47 +0700; I am doing the curve fitting using the non-linear regression (nls). I am not sure how to select the best model when I cannot get the AIC as in usual lm, glm, gam model. I cannot use the stepAIC func; /archives/html/s-news/2004-03/msg00033.html (6,718 bytes)
2. Re: question on nls (score: 1): Author: Spencer Graves <spencer.graves@pdf.com>; Date: Wed, 03 Mar 2004 16:19:07 -0800; Recall that nls assumes normal, independent errors. Thus, the prod( (1/(sigma*sqrt(2*pi))*exp(-0.5*(resid[i]/sigma)^2)). Therefore, the log(likelihood) is (-0.5)*( N*log(2*pi*sigma^2) + sum(resid[i]^; /archives/html/s-news/2004-03/msg00038.html (9,146 bytes)
3. Re: question on nls (score: 1): Author: Prof Brian Ripley <ripley@stats.ox.ac.uk>; Date: Thu, 4 Mar 2004 08:17:06 +0000 (GMT); My version of S-PLUS has nlme3 nlme3 nlme3 nlme3 nlme3 nlme3 "AIC.gls" "AIC.lm" "AIC.lmList" "AIC.lme" "AIC.logLik" "AIC.nls" so I think all you need to do is to call AIC on the fitted object. I beli; /archives/html/s-news/2004-03/msg00043.html (9,667 bytes)

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