[R-sig-ME] Specifying starting point for MCMCglmm()

[sree datta]

When you say 200 records, is this the total number of rows in the dataset?
What distribution are you assuming for your dependent variables? What
frequentist approach would you use instead of MCMC to model this data?

Sree

On Fri, Jun 5, 2020 at 3:59 PM Ruhs, Emily <ecruhs using usf.edu> wrote:

> Hi Sree~
>
> Thank you for reaching out.
>
>
>
> I am running 5 models that are near the form:
>
> EC1<-MCMCglmm(cbind(Infl.X, Infl.Y, Prop.Bottom, Prop.Top, Log.Slope,
> Coef) ~ (trait):log10Br+(trait):log10Bo,
>
>               random = ~us(trait):phylo, family=rep("gaussian", 6),
> rcov=~us(trait):units,
>
>               ginverse=list(phylo=inv.phyloEC$Ainv), prior=prior.1,
> data=speciesEC,
>
>               nitt=NITT*Mult,thin=THIN*Mult,burnin=BURN*Mult)
>
>
>
> I have 6 response variables and our models cover the full sweet of
> possibilities with log10Br and log10Bo as predictor variables (i.e. null
> model, log10Br alone, log10Bo alone, log10Br+log10Bo, log10Br*log10Bo). I
> have about 200 records (species) in the dataset.
>
>
>
> I’ve gotten results from the models using
> Mult=7;NITT=260000;THIN=200;BURN=60000, but when we plot the trace and
> density, they still do not appear to be converging. Therefore I would like
> to extend to a Mult = 10.
>
>
>
> Therefore, I was hoping to use the start= command to extend the models,
> without having to restart them; however, maybe that isn’t possible. Any
> advice you can provide would be greatly appreciated!
>
> Best,
>
> *From: *sree datta <sreedta8 using gmail.com>
> *Date: *Friday, June 5, 2020 at 3:48 PM
> *To: *"Ruhs, Emily" <ecruhs using usf.edu>
> *Cc: *"r-sig-mixed-models using r-project.org" <r-sig-mixed-models using r-project.org
> >
> *Subject: *Re: [R-sig-ME] Specifying starting point for MCMCglmm()
>
>
>
> This email originated from outside of USF. Do not click links or open
> attachments unless you recognize the sender or understand the content is
> safe.
>
>
>
> Hi Emily
>
>
>
> What are the specifications of your data you are using in the model that
> it is taking so long (14 days)? How many variables and records are you
> using? Have you attempted to run the model with a smaller subset of the
> data? If yes, what were the results?
>
>
>
> Sree
>
>
>
>
>
> On Thu, Jun 4, 2020 at 4:10 PM Ruhs, Emily <ecruhs using usf.edu> wrote:
>
> Hi everyone~
>
> I am running a series of large models in R using MCMCglmm. After running
> the models for 14 days (complicated, multivariate models), I found that the
> models have not converged yet and I need to run more iterations. I know you
> can use the start= to specify a starting function, but I’m having
> difficulties getting the model to run.
>
> model_EC <- parLapply(cl=cl,listEC, function(i) {
>   MCMCglmm(i[[1]],
>            random = ~us(trait):phylo, family=rep("gaussian", 6),
> rcov=~us(trait):units,
>
>  ginverse=list(phylo=inv.phyloEC$Ainv),prior=prior.1,data=i[[2]],
> start=1820000,
>            nitt=2600000,thin=1400,burnin=0)})
>
> As the code is written, I have the start=1820000, which is where the last
> iteration left off. Can anyone explain what I’m doing wrong in specifying
> the start function?
>
> Any help or suggestions would be greatly appreciated!
>
> Best,
> Emily Cornelius Ruhs
> Postdoctoral Scholar
> University of South Florida
>
>
>
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