[R-sig-ME] R Consortium call for funding

Phillip Alday phillip@@ld@y @ending from mpi@nl
Tue Oct 2 11:48:12 CEST 2018

I'm a bit late to the game on this one, but I would second the votes for
flexible covariance structures as in nlme. Perhaps this could be done by
investing funds into the flexlambda work?

Regarding two other suggestions:

1. Julia-like speed. There are bridges between Julia and R, but this
still doesn't help me once I have a fitted model in Julia and want the R
mixed-models ecosystem (effects, car::Anova(), lmerTest, etc.) to
examine the model. It should however be possible to construct a merMod
object from the fit in Julia. Tools for doing this would be quite nice.
(This also seems like relatively low-hanging fruit for a Google summer
of code type project.)

2. Better confidence intervals and predictions for non-linear links. I
think some parts of this are implemented in the effects and emmeans
packages. In addition to a more extensive/complete implementation, this
seems like something where additional documentation and worked examples
comparing conditional and marginalized coefficients would be useful,
potentially as part of the GLMM FAQ.


On 09/26/2018 12:52 PM, Manuel Ramon wrote:
> I totally agree with you, Ben. I have to admit that all the tidyverse world
> has suppose a great improvement in the way I work with data, but in the
> end, almost all my analyses conclude with the nlme/lme4 packages. So I
> think it is worth investing funds and time on it.
> As suggested by others, the inclusion of the variance functions from nlme
> would be very useful. Also, some of the capabilities of the mixed.models in
> Julia language in terms of computation time and data size would be very
> welcome, but this latter it is probably very difficult (almost impossible)
> given that they are to different platforms.
> In any case, thanks for the initiative and I hope it will go ahead.
> Regards,
> Manuel
> On Tue, Sep 25, 2018 at 11:00 PM Ben Bolker <bbolker using gmail.com> wrote:
>> https://www.r-consortium.org/announcement/2018/09/25/fall-2018-isc-call-for-proposals
>> "What can you do to improve the R ecosystem and how can the R Consortium
>> help you do it?"
>>  The mixed-model ecosystem is admittedly a small part of the R
>> ecosystem, but I (biasedly) think it's an important one.
>>   If people have ideas & opinions about how a chunk of money on the
>> order of $10,000 could be valuably spent to improve the mixed-model
>> ecosystem in a way that would be appealing to a very broad audience of
>> useRs, please discuss.
>> The deadline for submitting a proposal is midnight PST, Sunday October
>> 31, 2018.
>>   cheers
>>    Ben Bolker
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