@ercbk.bsky.social

Github: https://github.com/ercbk Website: https://ericbook.netlify.app/ Mastodon: @erc_bk@fosstodon.org

just got out of a course design meeting and now I kinda want to poke the #rstats hivemind on something: is there a way/approach to dynamic/reactive alt-text in shiny apps? (yes, i'm posting before searching. roast in replies, i suppose)

In better news, John Oliver's three-day stint/stunt as a corporate villain on legendary soap opera "General Hospital" appears to be going... fucking brilliantly?? I have watched this clip on a loop for like 20 mins I really, truly need to see the full episodes NOW

Do you have a favourite resource on pair programming? Please drop a link 🙏 I'd like to do some pair programming with our student worker over the summer and he is a bit avoidant. Which is common - people don't like the idea of someone looking over their shoulder and judging them. #dataBS

If you have access to any the following stats software, would you be willing to run some chi squared tests on a handful of simulated datasets and send me results? I need to verify that that my R implementation of what other software does is correct. - Stata - SAS - StatXact - SPSS DM me :)

Help pls #rstats I'm using {mice} to impute values of factor variables. My end-goal is to keep one row per obs, with the most common imputed value being retained but there are ties I could keep imputing one additional value until the tie is broken, but is there another way to go about this?

I've made some big changes to the fastglm package with version 0.1.0 on cran: cran.r-project.org/package=fast... - updates that further improve speed - three new models for more complex outcome (neg binom, hurdle, zero infl) - First bias correction - big data support ** Details outlined below:

fastglm: Fast and Stable Fitting of Generalized Linear Models using 'RcppEigen'

Fits generalized linear models efficiently using 'RcppEigen'. The iteratively reweighted least squares implementation utilizes the step-halving approach of Marschner (2011) &lt;<a href="https://doi.or...

cran.r-project.org

I've been working with NCV this last week; it's a powerful tool for modelling data with dependencies that are poorly/inefficiently modelled via stochastic process priors like cov functions or low-rank smoothers. However, it's a complex topic, so I thought I'd summarize the key ideas in a thread 1/n

@tiddlydump.bsky.social · 4mo ago

Saw that "neighborhood cross validation" was recently added to `mgcv` but I haven't had the chance to kick the tires. It sounds useful, but the effort of setting up neighborhoods vs modeling the correlation directly is something I'll have to sit with! stat.ethz.ch/R-manual/R-d... #rstats