#mgcvchat
Live, measured metrics for the hashtag #mgcvchat from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #mgcvchat
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 · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 22:25 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 22:25 UTCNo related tags with measured usage found for #mgcvchat.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 22:25 UTCEverything below is measured over the latest 15 public posts (spanning ~29902 hours).
Posting hours (UTC) — busiest: 12:00
Languages: English (15)
Avg boosts / post: 2.3
Top of the latest posts
Preprint from Simon Wood on the new cross-validation smoothness estimation in #mgcv: https://arxiv.org/abs/2404.16490. It's a neat performant + data-efficient way to estimate GAMs based on complex CV splits (like spatial/temporal/phylo ones
spending some more time thinking about neighbourhood cross-validation in #mgcv (see original post here: https://calgary.converged.yt/articles/ncv.html), but for time series. Pretty nice to be able to get back to a yearly trend here without
📈 Yes you can do that in mgcv update big thanks to Zachary Susswein for spotting that my code was out of date in my neighbourhood cross-validation examples: https://calgary.converged.yt/articles/ncv.html https://calgary.converged.yt/articl
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/mgcvchat