distributions3
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
A side-by-side editorial comparison of mev and RStudio — release velocity, themes, recent moves, and the top alternatives to consider.
An extreme-value toolkit reorganised its whole API into prefixed families and tripled its estimator count.
mev provides likelihood-based inference for univariate and multivariate extreme value models — threshold selection, shape estimation, tail dependence and max-stable simulation. Version 2.0 was a deliberate reorganisation: every threshold-selection routine now carries a thselect. prefix, every stability plot a tstab. prefix, and every extremal-dependence measure an xdep. prefix, with the old names deprecated but mostly still working. The same release added a large batch of estimators — Stein-weighted GPD, roughly a dozen shape estimators, second-order regular variation, L-moment GPD and Weissman quantiles.
RStudio ships through release branches, and the notes are commit messages
RStudio's feed is a run of release-branch tags — Yellow Yarrow, Pacific Dogwood, Golden Wattle — each carrying a backported fix rather than an announced feature. The newest tag restores a Windows install rule that had been deleted alongside an unrelated winpty block, leaving the shipped installer without a 32-bit rsession binary and breaking 32-bit R entirely. What reaches users is legible only if you read the commit body.
mev provides likelihood-based inference for univariate and multivariate extreme value models — threshold selection, shape estimation, tail dependence and max-stable simulation. Version 2.0 was a deliberate reorganisation: every threshold-selection routine now carries a thselect. prefix, every stability plot a tstab. prefix, and every extremal-dependence measure an xdep. prefix, with the old names deprecated but mostly still working. The same release added a large batch of estimators — Stein-weighted GPD, roughly a dozen shape estimators, second-order regular variation, L-moment GPD and Weissman quantiles.
The package is consolidating into a reference implementation of the extreme-value literature rather than a collection of one-off routines. Sixteen threshold-selection methods now share standardised arguments and their own plot and print methods with automatic selection, which is the tell: the goal is comparability across methods, not just availability. Dependency reduction runs alongside, with distribution functions written in-package to drop evd and Rsolnp replacing nloptr in earlier releases.
Version 2.1 continued adding threshold-selection routines within the new naming scheme, so the next release most likely follows the same pattern — more estimators fitted to the established prefixes, plus fixes to the 2.0 renaming. The entries give no sign of a further structural change.
RStudio's feed is a run of release-branch tags — Yellow Yarrow, Pacific Dogwood, Golden Wattle — each carrying a backported fix rather than an announced feature. The newest tag restores a Windows install rule that had been deleted alongside an unrelated winpty block, leaving the shipped installer without a 32-bit rsession binary and breaking 32-bit R entirely. What reaches users is legible only if you read the commit body.
Two areas absorb nearly all the visible work: Windows packaging correctness and Posit Assistant plumbing — SHA-256 verification of assistant downloads, gating .positai/.claude ignore-file edits on the directories actually existing. Both read as cleanup after features landed elsewhere. The release-branch structure means the same fix often appears twice, once on main and once backported, so tag count overstates the pace of change.
Expect further Yellow Yarrow tags in the same shape — a single backported fix per tag, its description written for reviewers rather than users. Posit Assistant integration is the most likely source of the next visible change, since it is the only area here still gaining behavior rather than losing bugs.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either mev or RStudio.
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
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Holistics keeps fencing in the AI layer it spent the summer building.
Dovetail spent July opening doors to other tools and August making its own rooms easier to enter.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. RStudio is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. RStudio is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top mev alternatives in Analytics are ranked by recent ship velocity. Browse the "mev alternatives" section above for the current picks, or visit /alternatives/mev for the full list with editorial commentary on each.
Top RStudio alternatives in Analytics are ranked by recent ship velocity. Browse the "RStudio alternatives" section above for the current picks, or visit /alternatives/rstudio for the full list with editorial commentary on each.