#likelihood
Live, measured metrics for the hashtag #likelihood from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #likelihood
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · mastodon.online (Mastodon public tags API) · fetched 2026-09-27 11:04 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.online (Mastodon public search API) · fetched 2026-09-27 11:04 UTCLive pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-09-27 11:04 UTCEverything below is measured over the latest 40 public posts (spanning ~28224 hours).
Posting hours (UTC) — busiest: 18:00
Languages: English (39) · Lithuanian (1)
Avg boosts / post: 0.4
Top of the latest posts
fly51fly (@fly51fly) CMU 연구진의 논문 ‘Tail-Likelihood Reinforcement Learning’이 공개되었습니다. 강화학습에서 확률 분포의 꼬리(tail) 영역과 likelihood를 활용하는 학습 접근을 다루는 것으로 보이며, 희귀하지만 중요한 보상·행동 사례를 더 잘 최적화하는 방법론일 가능성이 있습니다. 트윗에는 논문 제목과 링크 외의 실험·구현 세부사항은 제공되지 않았습니다. http
Evaluating genetic diversity differences within a likelihood framework https://atlas.whatip.xyz/post.php?slug=evaluating-genetic-diversity-differences-within-a-likelihood-framework Quick take: <p>The study of genetic diversity has a rich hi
#statstab #584 How are the likelihood ratio, Wald, and Lagrange multiplier (score) tests different and/or similar? Thoughts: I don't recall why I saved this link. But might be useful. #likelihood #stata #wald #lagrange #inference https://st
What “likelihood” means
Wiktionary · Wikipedialikelihood/ˈlaɪklihʊd/
- nounThe probability of a specified outcome; the chance of something happening; probability; the state or degree of being probable.
A likelihood function gives the relative merit of various statistical models for describing a data set. Often the models being compared are parameterized by a parameter, with the parameter often written as θ, or they are parameterized by multiple parameters given as the components of a vector. For a probability function Pr[x | θ] that gives the probability of data x for a given model-specifying parameter θ, the likelihood is any function of θ equal to cPr[x | θ] for some positive value c.
“Likelihood function” on Wikipedia (CC BY-SA) →#likelihood across platforms
every network with a public tag surfaceFollow #likelihood straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/likelihood