#sarima

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

hashtag.org network · sponsored

Own #sarima

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.

$520.70/ year · 6-character #name
Claim #sarima$520.70/yrBuy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
1
Recent posts
Mastodon
Recent pace
Mastodon · last 1
0
Avg reactions / post
Mastodon · last 1
Reddit posts / month
Reddit search
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-09-01 17:45 UTC
0
08-26
0
08-27
0
08-28
0
08-29
0
08-30
0
08-31
0
09-01

0 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 2026-09-01 17:45 UTC

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-09-01 17:45 UTC

Everything below is measured over the latest 1 public posts.

Posting hours (UTC)

00:0012:0023:00

Languages: Russian (1)

Avg boosts / post: 0

Top of the latest posts

  • SARIMAX vs Экспоненциальное сглаживание: Когда простота побеждает Продолжаю рассказывать про первые шаги в моделировании временных рядов. В этой статье разбираю модели SARIMAX и Экспоненциальное сглаживание, с примерами картинок и кода. htt

    Habr@[email protected]002024-06-19 13:42 UTCView post →

What “sarima” means

Wikipedia

In time series analysis used in statistics and econometrics, autoregressive integrated moving average (ARIMA) and seasonal ARIMA (SARIMA) models are generalizations of the autoregressive moving average (ARMA) model to non-stationary series and periodic variation, respectively. All these models are fitted to time series in order to better understand it and predict future values. The purpose of these generalizations is to fit the data as well as possible. Specifically, ARMA assumes that the series

Autoregressive integrated moving average” on Wikipedia (CC BY-SA) →

#sarima across platforms

every network with a public tag surface

Follow #sarima 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/sarima