41,554 blogs · 4,654,352 posts Claim your blog

Record · corpus.blog/posts/01a0d24f-8d9f-7157-9cd8-45c304a191db

Calibration for everyone and every decision problem, maybe

Andrew Gelman · published 15 November 2024

A record is what was published and who pointed at it. The text of the post is not held here: read it at the source, or at its Wayback capture.

Read the post at statmodeling.stat.columbia.edu Wayback capture

0blogs citing

First cited: —
Most recent: —
Rank this month: not ranked
External links: 6
Words captured: 1,574

Cited by

No blog we hold has cited this post yet.

Links from this post

Link

Host

https://dl.acm.org/doi/pdf/10.1145/3406325.3451064

dl.acm.org

https://arxiv.org/abs/1609.05807

arxiv.org

https://proceedings.mlr.press/v80/hebert-johnson18a/hebert-johnson18a.pdf

proceedings.mlr.press

https://arxiv.org/pdf/2109.05389

arxiv.org

https://www.semanticscholar.org/paper/A-calibration-hierarchy-for-risk-models-was-from-to-calster-Nieboer/1a64fa5aa5975ee4dfed8070d1ac391b25e8a1e2

semanticscholar.org

https://proceedings.mlr.press/v238/feng24a/feng24a.pdf

proceedings.mlr.press

Elsewhere on statmodeling.stat.columbia.edu (1)

Calibration is sometimes sufficient for trusting predictions. What does this tell us when human experts use model predictions? Read at the source ↗

statmodeling.stat.columbia.edu