equatiomatic
equatiomatic copied to clipboard
datalorax
Convert models to LaTeX equations
Would this be able to pull large ODEs from model objects? In particular, ones used in the MRGsolve package?
Amazing package! Are there plans to have this support negative binomial models?
When using the argument `wrap = TRUE` for `lme4::lmer()` models with many random effects, the coefficients wrap fine, but not the specification of the distribution - the equation for $\alpha_j$
I know this package from https://bookdown.org/yihui/rmarkdown-cookbook/equatiomatic.html. Like the actual coefficent output, ``` #> $$ #> \operatorname{\widehat{mpg}} = 34.66 - 1.59(\operatorname{cyl}) - 0.02(\operatorname{disp}) #> $$ ``` Does this package support the...
It might be good to submit this to peer review at rOpenSci and JOSS. They have [a publishing partnership](https://ropensci.org/blog/2017/11/29/review-collaboration-mee/), and some universities look favorably on peer reviewed/published software for tenure...
Currently, you can pull out the mean structure at level 1, and if you don't specify anything it will do this automatically for any equation that has more than 3...
This is mostly just a checklist of the more important models we might want to support with fancy math. In theory, these are all supported automatically with broom (though we...
Hi! I'm using your package quite a lot as a requirement for a small package I use at my company, I was wondering if you were planning to submit again...
Hello! I am preparing a rather large release for gtsummary and running reverse dependency checks. The checks are timing out for equatiomatic. I took a look at your use in...
I have a question about the notation you are using for `lme4::lmer`. Consider [your example](https://datalorax.github.io/equatiomatic/articles/lme4-lmer.html#unconditional-models):  Why did you parameterize *multiple* variances for the random intercepts as $\sigma^2_{\alpha_j}$ for $j=1,...,J$...
