#LinearModels

Live, measured metrics for the hashtag #LinearModels from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
7
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 7
2
Avg reactions / post
Mastodon · last 7

Day-by-day usage

measured · mastodon.social (Mastodon public tags API) · fetched 2026-07-27 08:00 UTC
0
07-21
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · mastodon.social (Mastodon public search API) · fetched 2026-07-27 08:00 UTC

No related tags with measured usage found for #linearmodels.

Live pulse

measured · mastodon.social (Mastodon tag timeline) · fetched 2026-07-27 08:00 UTC

Everything below is measured over the latest 7 public posts (spanning ~32116 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (6) · German (1)

Avg boosts / post: 1.7

Top of the latest posts

  • "The Robust Beauty of Improper Linear Models in Decision Making" lives rent free in my mind. I think about this paper from 1979 ALL. THE. TIME! TL;DR: experts can make robust linear models by just picking a few salient features from their e

    David Colarusso@Colarusso♥ 6↻ 82023-01-09 19:29 UTCView post →

  • In today's lecture on #StatisticalModeling, I explained how to define meaningful non-orthogonal hypotheses/contrasts in (generalized) #LinearModels. I only learned about the difference between specifying a contrast matrix vs. a hypothesis m

    Daniel Heck@Daniel_Heck♥ 6↻ 12022-11-09 10:20 UTCView post →

  • ‼ Announcement: Online Unfold.jl workshop ‼ 📅 09.05.2025 💶 Free! 👉🏼 https://github.com/s-ccs/workshop_unfold_2025 ❓ rERPs, mass univariate models & deconvolution! If you are interested in combined #EEG / #EyeTracking, in natural experim

    Benedikt Ehinger@[email protected]♥ 2↻ 12025-04-15 13:22 UTCView post →

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/linearmodels