>>>>> "ronggui" == ronggui <[EMAIL PROTECTED]> >>>>> on Mon, 24 Oct 2005 10:09:30 +0800 writes:
ronggui> ======= 2005-10-24 09:55:32 ronggui> úÚ´ÅдÀº======= >> Hello, I'm a Korean researcher who have been started to >> learn the "R" package. >> >> I want to make gam model and AIC value of the model to >> compare several models. >> >> I did the GAM model, but there were error for AIC. >> SO, how can I do? pleas help me!!! >> >> >> I did like below; >> >> > a.fit <- gam(pi~ s(t1r), family = gaussian(link="log")) >> > summary(a.fit) >> > Family: gaussian >> > Link function: log >> > >> > Formula: >> > pi ~ s(t1r) >> > >> > Parametric coefficients: >> > Estimate std. err. t ratio Pr(>|t|) >> > constant 0.093105 0.005238 17.77 < 2.22e-16 >> > >> > Approximate significance of smooth terms: >> > edf chi.sq p-value >> > s(t1r) 1.833 24.153 0.00014213 >> > >> > R-sq.(adj) = 0.435 Deviance explained = 47.1% >> > GCV score = 0.0010938 Scale est. = 0.00099053 n = 30 ronggui> are you using the mgcv package? if you are,just ronggui> use a.fit$aic to get the aic. hmm, yes, and no: It's true what you say, BUT is not at all recommended in general: You should use the generic AIC() function rather than extracting components yourself. This is a general priniciple: If possible use 'extractor functions' to work on objects rather then relying on internal representations. This is particularly relevant for fitted models: Do use residuals(.), fitted(.), LogLik(.), AIC(.), vcov(.) etc etc! Now back to this problem: >> AIC(a.fit) >> Error in logLik(object) : no applicable method for "logLik" I can't reproduce this; Eun definitely needs to give more details, since the following works fine: > library(mgcv) > x <- 1:50 > set.seed(1) > y <- 2^(sin(x/10) + rnorm(50)) > a.fit <- gam(y ~ s(x), family = gaussian(link="log")) > summary(a.fit) Family: gaussian Link function: log Formula: y ~ s(x) Parametric coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.3171 0.1251 2.535 0.0147 * --- Signif. codes: ..........{UTF-8 code} Approximate significance of smooth terms: edf Est.rank F p-value s(x) 2.858 9.000 3.07 0.00576 ** --- Signif. codes: ............ R-sq.(adj) = 0.4 Deviance explained = 43.5% GCV score = 0.94391 Scale est. = 0.87107 n = 50 > AIC(a.fit) [1] 140.6937 > ______________________________________________ R-help@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