similar to: Model selection and model efficiency - Search for opinions

Hi all, I am quite new in the world of parallelization and I wonder if there is a way to increase the speed of creation of a parallel socket cluster. The time spend to include threads increase exponentially with the number of thread considered and I use of computer with two 8 cores CPU and thus showing a total of 32 threads in windows 7. Currently, I use the default parameters (type =

Dear R users, Since a long time now, I have the following error when I want to load the tcltk library in R 64 bit. Loading Tcl/Tk interface ...Error : .onLoad failed in loadNamespace() for 'tcltk', details: call: inDL(x, as.logical(local), as.logical(now), ...) error: unable to load shared object 'C:/Program Files/R/R-2.13.0/library/tcltk/libs/x64/tcltk.dll': LoadLibrary

Dear UseRs, Is there a way to define the lower-upper bounds for parameters fitted by optim using the Nelder-Mead method ? Thanks, Arnaud [[alternative HTML version deleted]]

Hello All; I need to run a multiple regression analysis and use Akaike's Information Criterion for model selection. I understand that this command will give the AIC value for specified models: AIC(object, ..., k = 2) with "..." meaning any other optional models for which I would like AIC values. But, how can I specify (in the place of "...") that I want R to

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, Since I installed the x64 version of R (v2.12.1), I got a problem with tcltk that I did not achieve to resolve. When loading the library, it gives me the following error message: Loading Tcl/Tk interface ...Error : .onLoad failed in loadNamespace() for 'tcltk', details: call: inDL(x, as.logical(local), as.logical(now), ...) error: unable to load shared object

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Thomas Petzoldt > Sent: 06 September 2005 06:34 > Cc: petzoldt at rcs.urz.tu-dresden.de; R-Help > Subject: Re: [R] model selection vs. H0 based testing > > > Hello, > > I wish to thank Douglas Bates very much for clarification and

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

Hello! I am using package "VAR". I've fitted my model: mymodel<-VAR(mydata,myp,type="const") I can extract the Log Liklihood for THE WHOLE MODEL: logLik(mymodel) How could I calculate (other than manually) the corresponding Akaike Information Criterion (AIC)? I tried AIC - but it does not take mymodel: AIC(mymodel) # numeric(0) Thank you! -- Dimitri Liakhovitski

hi folks, I'm trying to build a table that contains information about a series of General Linear Models in order to calculate Akaike weights and other measures to compare all models in the series. i have an issue with indexing models and extracting the information (loglikehood, AIC's, etc.) that I need to compile them into the table. Below is some sample code that illustrates my

Hello I?m need fitt growth curve with data length-age. I want to evaluate which is the function that best predicts my data, to do so I compare the Akaikes of different models. I'm now need to evaluate if changing the initial values changes the parameters and which do not allow to estimate the model. To do this I use the function nls(); and I randomize the initial values (real positive number).

Dear Listers, I got this message when compiling a package: * creating pgirmess-manual.tex ... OK * checking pgirmess-manual.text ... ERROR LaTex errors when creating DVI version. This typically indicates Rd problems. The message is quite explicit but I struggled a lot before understanding that the trouble comes from a single file "selMod.rd" among 44 topics. Even though I have

Dear list, I fitted the same GAM model using directly the function gam(mgcv) ... then as a parameter of another function that capture the warnings messages (see below). In the first case, there is no warning message printed, but in the last one, the function find two warning messages stating "matrix not positive definite" So my question is: Do I have to worry about those warnings and

Odette > Wondering how can I generate "Akaike weight" with 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

Dear useRs, In a thesis, I found a mention of the use of pairwise deletion in linear regression and GLM (binomial family). The author said that he has used R to do the statistics, but I did not find the option allowing pairwise deletion in both lm and glm functions. Is there somewhere a package allowing that ? Thanks, Arnaud [[alternative HTML version deleted]]

Hi all We have a 100kVA GE LP Series UPS. I can't find this series in the HCL, but other GE UPSes are listed. Would it be possible to somehow use NUT with this UPS? -- Vennlige hilsener / Best regards roy -- Roy Sigurd Karlsbakk (+47) 98013356 roy at karlsbakk.net http://blogg.karlsbakk.net/ GPG Public key: http://karlsbakk.net/roysigurdkarlsbakk.pubkey.txt -- I all pedagogikk er det

Hello all, I am trying to use stepwise procedure to select covariates in Cox model and use bootstrap to repeat stepwise selection, then record how many times variables are chosen by step() in bootstrap replications. When I use step() (or stepAIC) to do model selection, I got errors. Here is the part of my code for (j in 1:mm){ #<--mm=10 for (b in 1:nrow(reg.bs)){ #<--bootstrap 10

Good afternoon friends, I am implementing squid + squidguard the pfsense authenticating samba 4 version 4.4.4 And always I get this message in squidguard logs. 2016-06-20 17:30:55 [75446] (squidGuard): ldap_simple_bind_s failed: Strong(er) authentication required 2016-06-20 17:30:55 [75446] Added LDAP source: administrator 2016-06-20 17:30:55 [75446] (squidGuard): ldap_simple_bind_s failed:

Dear all, is there a way to extract individual likelihoods from a glm/lrm object? By individual likelihoods, I mean the likelihoods whose product give the overall likelihood of the model. I guess the code in the base package, used to compute the Akaike Information Criterion may help me. However, I couldn't figure it out, probably because I'm rather new to likelihood theory and ML

I have done the usual estimation of GARCH models, applied to my historical dataset (commodities futures) with a maximum likelihood function and selected the best model on the basis of information criteria such as Akaike and Bayes. Can somebody explain me please the calibration scheme for a GARCH model? I was not able to find a paper, dealing with exactly this algorithm for my case. I only