similar to: Akaike weight in R

Hi Uwe and all, Error message was: error in normalizePath(path) : path[1]: no such file to load Many thanks, Odette On Fri, Jan 23, 2009 at 1:22 AM, Uwe Ligges <ligges@statistik.tu-dortmund.de > wrote: > > > Odette Gaston wrote: > >> Hi folks, >> >> I am currently having the problem with using R 2.8.1 that I cannot install >> some of packages from

Hi folks, I am currently having the problem with using R 2.8.1 that I cannot install some of packages from CRAN or local drive and somebody may be able to help me. ex) faraway package and lme4 package. I have downloaded them in my hard drive as local, but still R was unable to find the package (message showed up as no such file). I could download most packages, but not all what I want. I showed

Dear all, Is it possible to generate AIC or something equivalent for nonlinear model estimated based on maximum log likelihood l in R? I used nls based on least squares to estimate, and therefore I cannot assess the quality of models with AIC. nlme seems good for only mixed models and mine is not mixed models. res <- nls(y ~ d*(x)^3+a*(x)^2+b*x+c, start=list(a=2, b=1,c=1,d=1), data=d) If

Dear R users (r-help@r-project.org), The definition of AIC (Akaike information criterion) for normal error models has just been changed. Please refer to the paper below on this matter. Eq.(22) is the new definition. The essential part is RSS(n+q+1)/(n-q-3); it is close to GCV. The paper is temporarily available at the "Papers In Press" place. Kunio Takezawa(2012): A Revision of

Dear all, does anyone have r code to perform model-averaging of regression parameters by Akaike weights, and/or to do all-possible-subsets lm modelling that reports parameter estimates, AICc and number of parameters for each model? I have been looking for these in the archive but found none. (I am aware that many of you would warn me against these methods advocated by Burnham and Anderson

I am using lm simulation in R and try to find the AICc and Akaike weight of the model. I searched out that using package "AICcmodavg" AICc is easily to get. I wonder how can I get the "Akaike weight", any function I can use to generate it? Thanks in advance. Sunny [[alternative HTML version deleted]]

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Hello all, i hope you don't mind my off topic question. i want to use the Akaike criterion for variable selection in a regression model. Does anyone know some basic literature about that topic? Especially I'm interested in answers to the following questions: 1. Has (and if so how has) the criterion to be modified, if i estimate the transformations of the variables too? 2. How is the

Please can you help me I have the following problem: I have selected an lm model through the step procedure which visualize for each step the AIC value; then I have calculated for the initial model and the selected one the AIC using the funnction AIC. The results are different.What's happened? Emilia Rocco Dipartimento di Statistica "G. Parenti" Università di Firenze e-mail:

Sorry Gentlemen and all. Now this is becoming a joke (to me). I repeated what I did earlier, with and without the option to set repos suggested by Duncan. Now it does not work. I wonder whether it is dependent on the mirror I chose, but I do not remember the one I chose earlier when it work. I need your help, gentlemen, as I need to use R-3.0.3 for my task. >

Thanks. You gentlemen please tell me what this means. In R (outside of RStudio) I ran: install.packages("aod") Received a warning (and installation did not seem to go through). Then I tried install.packages("aod",repos='https://cran-archive.r-project.org') Received a warning but it went on to try

Hello, first of all I have found lots of different versions of the FPE which have given me different results. I was wondering if there was an explicit command in R to compute the FPE of a model. Thank you in advance, Jonny -- View this message in context: http://r.789695.n4.nabble.com/Akaike-s-Final-Prediction-Error-FPE-tp4519011p4519011.html Sent from the R help mailing list archive at

Thanks for the help. I have a reason to continue with R-3.0.3. I used maxLik to estimate econometric models and some of them are better handled with R-3.0.3 (but not later)----a sad reality I do not like. Here is what I did. I downloaded https://cran-archive.r-project.org/bin/windows/contrib/3.0/aod_1.3.zip and installed the zip file, which worked in both RStudio and R (without RStudio). In

He didn't specify the RStudio repos, though it's probably implicitly specified in getOption("repos"). I wonder why install.packages() is looking there, when repos is given explicitly? On 08/10/2020 8:54 a.m., Uwe Ligges wrote: > Drop the RStudio repos. > > Best, > Uwe Ligges > > On 05.10.2020 11:10, Steven Yen wrote: >> Thanks. I did as suggested but

Dear all, I found a problem with 'lme4'. Basically, once you load the package 'aod' (Analysis of Overdispersed Data), the functions 'lmer' and 'glmer' don't work anymore: library(lme4) (fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)) (gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd), family = binomial, data

Thanks for the help. I do update to the latest R-4.0.2. As I said, for reasons that's hard to explain, some of my tasks are better handled with an older version of R, in this case R-3.0.3. Please just help me install packages successfully with this older version of R. I ran the following line but obviously was not getting it across. ===== >

Okay, so it's not an RStudio issue. However, I'd guess setting options(repos = "https://cran-archive.r-project.org") at the start of your session could make everything work. (I'm guessing you currently have it set to "http://cran.rstudio.com", which is the source of the last warning below, probably due to an R bug. But since you're using an obsolete

Thanks. I did as suggested but still received a warning, though the installation went through. Anything I could do to install without the warning message. What is the contrib.url argument? > install.packages("aod",repos='https://cran-archive.r-project.org') Warning in install.packages : ? unable to access index for repository

Don't choose a mirror. That will override the repos choice. Do update R to a current version if you aren't able to debug this yourself. Duncan Murdoch On 08/10/2020 12:38 p.m., Steven Yen wrote: > Sorry Gentlemen and all. Now this is becoming a joke (to me). I repeated > what I did earlier, with and without the option to set repos suggested > by Duncan. Now it does not work.

All support on this list is voluntary, and support for old versions of R is not even necessarily on-topic here which is why you keep getting nudged to upgrade. Your "need" for support for an old version is definitely not "our" problem, so I suggest you start looking for a consultant if this issue is that important to you. Such is the nature of volunteer-developed open source