similar to: pMCMC and HPD in MCMCglmm

Hi, Thanks in advance for any help on this question. I'm running multinomial models using the MCMCglmm package. The models have 5 outcome variables (each with count data), and an additional two random effects built into the models. The issue is that when I use the following code, the summary only gives me results for four of the outcome variables. Here is the code for my model: m3.random

> On Mar 22, 2018, at 1:31 PM, Michelle Kline <michelle.ann.kline at gmail.com> wrote: > > Hi, > > Thanks in advance for any help on this question. I'm running multinomial > models using the MCMCglmm package. The models have 5 outcome variables > (each with count data), and an additional two random effects built into the > models. The issue is that when I use

Dear R users,   I need to draw a barplot with 2 Y axis. I have 3 days each of wich having 2 groups (and error bar for each of them). The height of the 3rd day is too tall compared to others. That's why I have to use a second Y axis for that. I am using  "barplot2" function of "gplots" library (to be able to add error bars as well). Data and  codes currently I am using is

Hi David, Thanks for your comment. I haven't posted the data because they are unpublished and include human subjects so there are issues with sharing on a list serv, but I thought perhaps someone had encountered a similar problem and would already know the answer. I will reconsider whether my University's ethics approval would allow me to post the data and update the question if I think

Hello, I get a nice looking barplot using the barplot2 function in the gregmisc package: body2 <- barplot2(hh3, beside = TRUE, col = c("mistyrose", "lightcyan"), .... cex.names = 1.0, plot.ci = TRUE, ci.l = cil, ci.u = ciu, plot.grid = TRUE) box() However, obviously I lose the collors when converting from ps to a pdf (outside of R)

Hi everyone, Apologies if this is a silly question but I am a student and this is my first time using R so I am still trying to educate myself on commands, models e.t.c I have a mixed model with four dichotomous fixed factors and subject as a random factor (as each person completed four vignettes, with factors crossed across vignettes). I have run an lmer model and used the Monte Carlo method

-------------------------------------------------- From: "Ahoussou Sylvie" <sylvie.ahoussou at antilles.inra.fr> Sent: Friday, September 12, 2008 9:48 AM To: "Thomas Lumley" <tlumley at u.washington.edu> Subject: Re: [R] Complex sampling survey _ Use of survey package > Thanks for your answer > > I think I made a mistake when I recopied the 5 first rows of

Hello everybody I don't understand how I'm supposed to use svydesign caracteristics to explain to R that my sampling design is the following one Data base = tab1 here are the five first rows of the database (nrow = 11792) num esp Quarters Totcat Totshp Totgt Tbtpos fpc1 Totanim Id_An 10 2045 G

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA512 hi, on OS X, when you try and use something which depends on X11, and you don't have XQuartz installed, you receive an error message, it directs you to download XQuartz, and then it euthanizes your process. (my guess is that there is a skeleton X11 dylib installed in OS X by default, and it is responsible for the error message and the

Hello, I was wondering, is there a way to plot estimated betas and standard deviations that I've generated? Specifically, I have the following: A matrix of estimated betas (two different betas, 4 different simulations - categories). A matrix of estimated standard errors corresponding to each of those betas. I would like to plot the estimated beta, and make a confidence

Dear colleagues, I?m a new R-help user. I?ve read the advertisements about the good manners and I hope to propose a good question. I?m using R to build an epidemiological SEIR model based on ODEs. The odesolve package is very useful to solve deterministic ODE systems but I?d like to perform a stochastic simulation based on Markov chain Montecarlo methods. I don?t know which packages could be

Dear R users, I'd like to known your opinion about a problem with anova.lmRob() of "Robust" package that occurs when I run a lmRob() regression on my dataset. I check my univariate model by single object anova as anova(lmRob(y~x)). If I compare my model with the null model (y~1), I must obtain the same results, but not for my data. Is it possible? My example:

Hi, I have a question about how I should report the results for a linear mixed effects model where the model includes as predictors three factors (facA, facB and facC), one of which (facA) interacts with the other two. facA and facB have two levels and facC has 3 levels. There are also several other continuous predictors (e.g. varA, varB, varC). My mixed model is specified with the following

Version 3.9 of the survey package is now on CRAN. Since the last announcement (version 3.6-11, about a year ago) the main changes are - Database-backed survey objects: the data can live in a SQLite (or other DBI-compatible) database and be loaded as needed. - Ordinal logistic regression - Support for the 'mitools' package and multiply-imputed data - Conditioning plots,

Version 3.9 of the survey package is now on CRAN. Since the last announcement (version 3.6-11, about a year ago) the main changes are - Database-backed survey objects: the data can live in a SQLite (or other DBI-compatible) database and be loaded as needed. - Ordinal logistic regression - Support for the 'mitools' package and multiply-imputed data - Conditioning plots,

I'm sorry, maybe the question was bad posed. Ista has well described my problem. Thanks Massimo >----Messaggio originale---- >Da: izahn at psych.rochester.edu >Data: 28/07/2011 17.52 >A: "David Winsemius"<dwinsemius at comcast.net> >Cc: "m.fenati at libero.it"<m.fenati at libero.it>, <r-help at r-project.org> >Ogg: Re: [R]

We can't and don't need to try resuming the device from our hotplug handlers, but hotplug events are generally something we'd like to keep the device awake for whenever possible. So, grab a PM ref safely in our hotplug handlers using pm_runtime_get_noresume() and mark the device as busy once we're finished. Signed-off-by: Lyude Paul <lyude at redhat.com> Cc: stable at

We can't and don't need to try resuming the device from our hotplug handlers, but hotplug events are generally something we'd like to keep the device awake for whenever possible. So, grab a PM ref safely in our hotplug handlers using pm_runtime_get_noresume() and mark the device as busy once we're finished. Signed-off-by: Lyude Paul <lyude at redhat.com> Cc: stable at

On Tue, Sep 3, 2019 at 4:49 PM Lyude Paul <lyude at redhat.com> wrote: > > Since we're going to be reprobing the entire topology state on resume > now using sideband transactions, we need to ensure that we actually have > short HPD irqs enabled before calling drm_dp_mst_topology_mgr_resume(). > So, do that. > > Cc: Juston Li <juston.li at intel.com> > Cc:

Since we're going to be reprobing the entire topology state on resume now using sideband transactions, we need to ensure that we actually have short HPD irqs enabled before calling drm_dp_mst_topology_mgr_resume(). So, do that. Cc: Juston Li <juston.li at intel.com> Cc: Imre Deak <imre.deak at intel.com> Cc: Ville Syrjälä <ville.syrjala at linux.intel.com> Cc: Harry Wentland