search for: aic

...nsistent results until I switched to R 3.3.2. * Comparing results from environments 1, 2, and 3 shows that changing the version of the gam package did not change the results under R 3.3.0. * Comparing results from environments 3 and 4 shows that changing the version of R altered the values of the AIC and the output of the step.gam call (changed to a NULL object) * Comparing results from environments 4 and 5 shows that reverting to an older version of the gam package in R 3.3.2 still produced altered AIC values and the NULL output from step.gam call Further investigations into these differenc...

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....ALC<-gam(X143S~ALC,data=dane,family=binomial) > step.gam.ALC<-step.gam(gam.object.ALC,scope=list("ALC"=~1+ALC+s(ALC,2)+s(ALC,3)+s(ALC,4)+s(ALC,6)+s(ALC,8)+lo(ALC,degree=1,span=.5)+lo(ALC,degree=2,span=.5)+lo(ALC,degree=1,span=.25)+lo(ALC,degree=2,span=.25))) Start: X143S ~ ALC; AIC= 104.0815 Trial: X143S ~ 1; AIC= 111.1054 Trial: X143S ~ s(ALC, 2); AIC= 103.3325 Step : X143S ~ s(ALC, 2) ; AIC= 103.3325 Trial: X143S ~ s(ALC, 3); AIC= 102.9598 Step : X143S ~ s(ALC, 3) ; AIC= 102.9598 Trial: X143S ~ s(ALC, 4); AIC= 102.2103 Step : X143S ~ s(ALC, 4) ; AIC= 102.2103...

Dear R collegues, I'm trying to understand what's AIC in R (ver. 1.3.1), and I'm getting a different answer if I look at the AIC(of the fitted model) or the aic in the summary( of the fitted model). Is this correct? Can somebody explain me the difference between the two values? or Is the AIC criterion not appropiated for Poisson models? R session...

Dear R collegues, I'm trying to understand what's AIC in R (ver. 1.3.1), and I'm getting a different answer if I look at the AIC(of the fitted model) or the aic in the summary( of the fitted model). Is this correct? Can somebody explain me the difference between the two values? or Is the AIC criterion not appropiated for Poisson models? R session...

I am running a series of candidate mixed models using lmer (package lme4) and I'd like to be able to compile a list of the AIC scores for those models so that I can quickly summarize and rank the models by AIC. When I do logistic regression, I can easily generate this kind of list by creating the model objects using glm, and doing: > md <- c("md1.lr", "md2.lr", "md3.lr") > aic <-...

...ng my computational work I encountered unexpected behavior when calling "ar" function, namely # time series x<-ts(c(-0.2052083,-0.3764986,-0.3762448,0.3740089,0.2737568,2.8235722,- 1.7783313,0.2728676,-0.3273164),start=c(1978,3),frequency=4,end=c(1980,3)) # ar function res.ar<-ar(x,aic=TRUE,demean=F) # call "ar" again and ............ res.ar<-ar(x,aic=TRUE,demean=F) Error in if (order > 0) coefs[order, 1:order] else numeric(0) : missing value where TRUE/FALSE needed In addition: Warning messages: 1: In log(var.pred) : NaNs produced 2: In if (order > 0) coefs...

just one other thing about the AIC issue: there is a line in glm.fit which is the following: aic = aic(y, n, mu, weights, dev) + 2 * rank but I couldn't find the function aic so I couldn't investigate further. It looks suspicious though because it seems to me like it should be aic = -2*likelihood + 2 * rank if anyone c...

I would like to figure out the equations for calculating "AIC" in both "step() function" and "AIC () function". They are different. Then I just type "step" in the R console, and found the "AIC" used in "step() function" is "extractAIC". I went to the R help, and found: "The criterion...

I know this a newbie question, but I've only just started using AIC for model comparison and after a bunch of different keyword searches I've failed to find a page laying out what the differences are between the AIC scores assigned by AIC() and mle.aic() using default settings. I started by using mle.aic() to find the best submodels, but then I wanted to als...

R 2.3.0, all packages up to date Linux, SuSE 10.0 Hi I want to calculate AIC or BIC from several results from mle calculation. I found the AIC function, but it does not seem to work with objects of class mle - If I execute the following: ml1 <- mle(...) AIC(ml1) I get the following error messale: Error in logLik(object) : no applicable method for "logLik" Th...

Hello. I need to know how can R compute AIC when I study a regression model? For example, if I use these data: growth tannin 1 12 0 2 10 1 3 8 2 4 11 3 5 6 4 6 7 5 7 2 6 8 3 7 9 3 8 and I do model <- lm (growth ~ tannin) AIC(model) R responses: 38.7...

I'm trying to add arguments to the AIC method for some classes -- things like weights=TRUE to calculate AIC weights corr=TRUE, nobs to calculate AICc delta=TRUE to put a delta-AIC column in the output. The problem is that AIC is defined as AIC(object, ..., k=2) where k is the constant associated with the penalty term and ... i...

Could someone please tell me how to stop the package/function name from being included before the command prompt? This started happening today after I made some changes to my Rprofile.site file and I don't know why. For example: if I enter example(AIC), instead of just getting the regular '>' before each output line, I get 'AIC>' instead. I only want the '>' and have searched everywhere and can't find an option to change this. Thanks David ----------------------- AIC> lm1 <- lm(Fertility ~...

I would like test AICc as a criteria for model selection for a glm using stepAIC() from MASS package. Based on various information available in WEB, stepAIC() use extractAIC() to get the criteria used for model selection. I have created a new extractAIC() function (and extractAIC.glm() and extractAIC.lm() ones) tha...

Is it generally known/has it been previously discussed here that the $aic() component in GLM-family objects (e.g. results of binomial(), poisson(), etc.) does not as implemented actually return the AIC, but rather -2*log-likelihood + 2*(model_has_scale_parameter) ? Can anyone in this forum gauge how a documentation patch would be received? This behaviour does not seem...

...code of chapter 8. Cheers, Ben -------------------------------------------------------------------------------- Pseudo code -------------------------------------------------------------------------------- Define RSS as: RSS = (1-alpha)*RSS(identification set) + alpha* RSS(validation set) and AIC as: AIC = 2*np + N*log(RSS) where np corresponds to the non-null parameters of the neural network and N is the sample size (based on http://en.wikipedia.org/wiki/Akaike_information_criterion). Assuming a feed-forward neural network with a single hidden layer and a maximum number of neurons (maxSi...

...rends. I would like to compare different models using GLM, GLMM, GAM and GAMM, basically do demonstrate the added value of GAMs/GAMMs relative to GLMs/GLMMs, by fitting splines. GLMMs/GAMMs are used to possibly improve fits from GLMs/GAMs by accounting for serial dependence. My idea is to use AIC to compare the different models. I’ve noticed that when setting up two seemingly identical models using the two functions gam (of the package mgcv) and gamm4 (of the package with same name), the AIC turns out to be different: > gam.0<-gam(dv ~ s(hours24,fx=F,k=-1,bs=“cc“),method=&qu...

...39; rcs(NDWI, knots)NDWI'' rcs(NDWI, knots)NDWI''' 0.02067 0.08441 -0.54307 3.99550 -17.38573 Degrees of Freedom: 700 Total (i.e. Null); 696 Residual Null Deviance: 33.25 Residual Deviance: 31.76 AIC: -167.7 A negative AIC occurs! How can the negative AIC from different models be compared with each other? Is this result logical? Is the lowest AIC still correct? Thanks, Jan _______________________________________________________________________ ir. Jan Verbesselt Research Associate Lab o...

...ith R? I know the description, > but is there any function to generate by R on the web-site or R library? > I am using GLM or GLMM (family=binomial), so would be appreciated if you > help me. You could have a look at this. http://bm2.genes.nig.ac.jp/RGM2/R_current/library/aod/man/summary.aic.html Which is in the OAD package Graham