similar to: "glmulti": excluding intractions between variables

Displaying 20 results from an estimated 600 matches similar to: ""glmulti": excluding intractions between variables"

2010 Aug 03
1
"glmulti": defining which intractions between variables are to be included
Hello, I'm using the "glmulti" package to run models of all the possible combinations of my variables. However, I am only interested in a few interactions between my variables. I have tried the equivalent of: mod1<-lm(y~a+b+c+a:b) glmulti(mod1, level=1) mod2<-lm(y~a+b+c+a:b) glmulti(mod2, level=2) and glmulti("y", c("a", "b", "c"),
2010 Aug 25
0
package MuMIn
[cc'ing back to r-help: this is good etiquette so that the responses will be seen by others/ archived for future reference.] On 10-08-25 04:35 PM, Marino Taussig De Bodonia, Agnese wrote: > Yes, I meant "MuMIn" > > the global formula I introduced was: > > rc4.mod<-lm(central$hunting~ central$year + central$gender + central$hunter + central$k.score +
2010 Jul 06
1
PCA and Regression
Hello, I am currently analyzing responses to questionnaires about general attitudes. I have performed a PCA on my data, and have retained two Principal Components. Now I would like to use the scores of both the principal comonents in a multiple regression. I would like to know if it makes sense to use the scores of one principal component to explain the variance in the scores of another principal
2010 Aug 24
2
chisq.test on samples of different lengths
Hello, I am trying to see whether there has been a significant difference in whether people experienced damages from wildlife in two different years. I therefore have two columns: year 1: yes no no no yes yes no year 2: no yes no yes I wanted to do a chisq.test, but if I enter it this way: chisq.test(year1, year2) I get the error saying the columns are two different lengths. So then I tried
2012 Sep 02
1
glmulti runs indefinitely when using genetic algorithm with lme4
Dear List, I'm using glmulti for model averaging in R. There are ~10 variables in my model, making exhaustive screening impractical - I therefore need to use the genetic algorithm (GA) (call: method = "g"). I need to include random effects so I'm using glmulti as a wrapper for lme4. Methods for doing this are available here
2018 Jan 31
0
MICE data analysis with glmulti
Dear All, wonder if you have some thoughts on running the with() function (and perhaps including the pool() function to get the results?) in glmulti? In other words, how to run glmulti with a data set that is produced by mice()? publicly available code: data <- airquality data[4:10,3] <- rep(NA,7) data[1:5,4] <- NA data <- data[-c(5,6)] library(mice) library(glmulti) the following
2013 Apr 17
0
Multi-core processing in glmulti
Dear list, I am trying to do an automated model selection of a glmm (function glmer; package: lme4) containing a large number of predictors. As far as i understand, glmulti is able to devide the process into chuncks and proceed by parallel processing on on multiple cores. Unfortunately this does not seem to work and i could not really fid any advice on the matter on other forums. Specifically i
2012 Nov 08
1
Package "glmulti": Include a variable in ALL models
Dear all, I have a question about the glmulti package. I want to include some variables in all models. To that end I applied the wrapper function as shown in the examples (http://www.inside-r.org/packages/cran/glmulti/docs/glmulti). To include the variable "Geslacht" in all models: > glm.redefined = function(formula, data, always="", ...)
2011 Nov 23
1
glmulti fails because of rJava
Dear R, The glmulti package no longer loads through the library() command, apparently because of a problem with rJava. I have today reinstalled R from scratch (updated to v2.14.0) and reinstalled all packages from scratch and updated them all too. The problem is the same as I found on v2.13.2. See session below for the error. I tried install.packages(rJava) as advised by the error report but it
2012 Sep 11
1
using alternative models in glmulti
All, I am working on a multiple-regression meta-analysis and have too many alternative models to fit by hand. I am using the "metafor" package in R, which generates AIC scores among other metrics. I'm using a simple formula to define these models. For example, rma(Effect_size,variance, mods=~Myco_type + N.type +total, method="ML")->mod where Effect_size is the
2011 Nov 21
0
rJava and multicore
Hello MasteRs- Because I want to parallelize several calls to the glmulti package, what I'm essentially doing is trying to parallelize different calls to rJava. I'm using plyr functions which use foreach and then doMC which means multicore is my backend for parallelizing. I've tried several approaches to this but have not succeeded, i also find virtually no record of folks trying
2019 Oct 16
0
vfs_recycle permission bug?!
Hai Marco, Can you check this acl and attr are these installed? type acl type attr Or just run : apt-get install -y acl attr Try this : chmod 1770 /srv/work/.cestino/ Which sets : "creator Owner" (1), Owner (7), Group (7), World (0) So the owner and groups can create anything but your enforcing "creator owner" Then set: recycle:subdir_mode = 1700
2013 Apr 15
1
Optimisation and NaN Errors using clm() and clmm()
Dear List, I am using both the clm() and clmm() functions from the R package 'ordinal'. I am fitting an ordinal dependent variable with 5 categories to 9 continuous predictors, all of which have been normalised (mean subtracted then divided by standard deviation), using a probit link function. From this global model I am generating a confidence set of 200 models using clm() and the
2019 Oct 16
4
vfs_recycle permission bug?!
Samba 4.8 (Louis debian repo), DM. Today i've had to recovery a deleted file in that share, that use 'vfs_recycle' modules: [Work] comment = Spazio di Lavoro Utente map acl inherit = Yes path = /srv/work read only = No store dos attributes = Yes vfs objects = acl_xattr recycle full_audit volume = Work full_audit:failure = none full_audit:success = mkdir rmdir read pread
2010 Apr 21
1
Best subset of models for glm.nb()
Dear List, I am looking for a function that will find the best subset of negative binomial models. I have a large data set with 15 variables that I am interested in. I want an easy way to run all possible models and find a subset of the "best" models that I can then look at in more detail. I have found two functions that seem to provide what I am looking for, but am not sure which
2010 Aug 12
1
multicore mclapply error
I'm running r 2. on a mac running 10.6.4 and a dual-core macbook pro. I'm having a funny time with multicore. When I run it with 2 cores, mclapply, R borks with the following error. The process has forked and you cannot use this CoreFoundation functionality safely. You MUST exec(). Break on __THE_PROCESS_HAS_FORKED_AND_YOU_CANNOT_USE_THIS_COREFOUNDATION_FUNCTIONALITY___YOU_MUST_EXEC__()
2011 Oct 21
2
glm-poisson fitting 400.000 records
Hi, I am trying to fi a glm-poisson model to 400.000 records. I have tried biglm and glmulti but i have problems... can it really be the case that 400.000 are too many records??? I am thinking of using random samples of my dataset..... Many thanks, -- View this message in context: http://r.789695.n4.nabble.com/glm-poisson-fitting-400-000-records-tp3925100p3925100.html Sent from the R help
2004 Aug 21
1
IAX2 DTMF not recognized - Bug report - Help sought
I have working SIP numbers with broadvoice, and just added a DID from http://connect.voicepulse.com/ . The calls answer, but DTMF is not recognized. With "iax2 debug" active pressing DTMF does nothing. Zilch. Zero. A friend tried a different IAX2 connection, and got the same results. I see the following in the archives: On Fri, 2004-04-09 at 10:12, Robert Jackson wrote: > Hey
2012 Apr 07
0
Resumen de R-help-es, Vol 38, Envío 13
2012/4/7 <r-help-es-request@r-project.org> > Envíe los mensajes para la lista R-help-es a > r-help-es@r-project.org > > Para subscribirse o anular su subscripción a través de la WEB > https://stat.ethz.ch/mailman/listinfo/r-help-es > > O por correo electrónico, enviando un mensaje con el texto "help" en > el asunto (subject) o en el cuerpo a:
2012 Sep 19
0
Lowest AIC after stepAIC can be lowered by manual reduction of variables (Florian Moser)
A few general comments about stepwiseAIC and a suggestion of how to select models a) Apart form the problem, that stepwise selection is not a garanty to get the best model, you need to have a lot of data to avoid overfitting if your model includes 7 parameter plus interactions (> 10 observations per parameter is what you are ideally looking for). b) Have a look at Anderson and Burnham's