BLUE
SW
Stephen Wild
@stephenjwild.bsky.social
I try to put straight lines through things but usually fail. Try to be Bayesian when I can. Views my own. RT/like != endorsement.
957 followers492 following1k posts
Reposted by Stephen Wild
AVavehtari.bsky.social

The most recent brms CRAN version added support for loo_epred() and moment matching for LOO-CV predictions, which makes it easy to make, for example, predictive probability calibration plots using the LOO-CV predictions #Bayesian#rstats

rd<-reliabilitydiag(EMOS = loo_epred(fit), y = df$y)
autoplot(rd) +
  labs(x = "Predicted (LOO)", y = "Conditional event probabilities")
0
SWstephenjwild.bsky.social

Feel free to keep spamming! This stuff is neat

0
SWstephenjwild.bsky.social

Thanks!

0
SWstephenjwild.bsky.social

I am always inconsistent in my use of leading zeros 🤪

0
SWstephenjwild.bsky.social

Good suggestions. I shall take them. I'm intentionally trying to avoid using as much jargon as I can, but I think you're right about dropping in some terms often used in the context of DAGs. Thanks!

0
SWstephenjwild.bsky.social

Do you have any good references for assessing the quality of spatially-referenced indices?

1
Reposted by Stephen Wild
MNmichelnivard.bsky.social

Overcomplete models, with more latent than observed variables, model complexity that traditional methods (PCA, SEM & ICA) can't uncover. A tutorial how to fit over-complete models in MCMSEM. MAny potential applications in epi, neuro, genetics & Psych🧠📊 Check it out: rpubs.com/MichelNivard...

3
SWstephenjwild.bsky.social

No. Some of us are just part of the landscape.

1
SWstephenjwild.bsky.social

Definitions and measurement are a mess in this area too

0
SW
Stephen Wild
@stephenjwild.bsky.social
I try to put straight lines through things but usually fail. Try to be Bayesian when I can. Views my own. RT/like != endorsement.
957 followers492 following1k posts