Dear Ting-Wen.

Yes, if "R thinks optimization may have not converged" you should run 
optimization again. Indeed, it may be wise to do this /even if/ R thinks 
optimization _has_ converged (R can be wrong).

If you are using /fitMk/ in /phytools/, you must set the argument 
/rand_start=TRUE/ to ensure that each optimization is starting from a 
different set of initial values.

There are lot of examples of how to do this efficiently available 
online. For example:

1. Running multiple optimization iterations of /fitMk/ in parallel using 
the /foreach/ package: 
http://blog.phytools.org/2024/04/another-post-about-running-multiple.html.

2. Running multiple parallelized optimizations (in series) using 
/fitMk.parallel/: http://www.phytools.org/Rbook/6/corrections.html.

(There are lots of other examples on my blog: http://blog.phytools.org/.)

Best wishes, Liam

Liam J. Revell
Professor of Biology, University of Massachusetts Boston
Web: http://faculty.umb.edu/liam.revell/
Book: Phylogenetic Comparative Methods in R 
<https://press.princeton.edu/books/phylogenetic-comparative-methods-in-r> 
(/Princeton University Press/, 2022)


On 11/11/2024 6:28 AM, Chen, Ting-Wen wrote:
> CAUTION: EXTERNAL SENDER
>
> Dear experts in phylogenetic comparative methods,
>
> When I ran the fitMk function from phytools (actually the fitMk.parallel I 
> was using), I got a message saying "R thinks optimization may not have 
> converged”.
>
> Would this be a problem if I continue to use the Qmatrix generated by fitMk 
> for downstream analysis such as simmap? Or how can I fix this by letting the 
> function run longer until it finds a better solution?
>
> Thank you very much in advance!
>
>
> Kind regards
> Ting-Wen
>
> --
> Ph.D. Ting-Wen Chen
> Animal Ecology (AG Scheu)
> J.F. Blumenbach Institute of Zoology and Anthropology
> Georg August Universität Göttingen
> Untere Karspüle 2
> D-37073 Göttingen, Germany
> https://www.uni-goettingen.de/en/348915.html
>
>
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