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hydroloom vs mev

A side-by-side editorial comparison of hydroloom and mev — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

hydroloom vs mev: at a glance

Featurehydroloommev
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themeshydrology, network-analysis, geospatial, r-packageextreme-value-theory, threshold-selection, statistical-estimation, api-redesign
Last editorial update5h ago44m ago
WebsiteVisit →Visit →

What is hydroloom?

USGS puts a type system over its river network toolkit so errors surface at dispatch

hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.

Read the full hydroloom trajectory →

What is mev?

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.

Read the full mev trajectory →

hydroloom vs mev: editorial side-by-side

H
hydroloom
ANALYTICS
0.0

USGS puts a type system over its river network toolkit so errors surface at dispatch

◆ Current state

hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.

◆ Where it's heading

The package spent its first releases porting and broadening — non-dendritic network support, divergence routing, subsetting that follows diversions out of a basin — and has now turned to making that surface safe to use. The class hierarchy is the structural expression of that turn: instead of every function re-checking whether a data frame has the columns it needs, the type carries the guarantee. The explicit outlet rule resolves a category of failure where valid networks errored on NA or orphan toid values.

◆ Prediction

The release notes flag that subclass attributes are stripped by standard dplyr operations, which is the kind of rough edge that usually generates follow-up work — expect attribute preservation or restoration helpers next.

M
mev
ANALYTICS
0.0

An extreme-value toolkit reorganised its whole API into prefixed families and tripled its estimator count.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

Alternatives to hydroloom and mev

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 hydroloom or mev.

See all hydroloom alternatives → · See all mev alternatives →

Recent activity from hydroloom and mev

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 2mo agohydroloomhydroloom v1.2.0
  2. 5mo agohydroloomTest tolerances relaxed for CRAN Fedora checks
  3. 5mo agohydroloomNetwork subsetting and divergence-routed accumulation
  4. 9mo agomevTwo more threshold-selection routines slot into the new scheme
  5. 9mo agomevThreshold, stability and dependence functions regrouped under prefixes
  6. 10mo agohydroloomSort and indexing fixes
  7. 1y agohydroloomUpmain and downmain navigation for non-dendritic networks
  8. 2y agomevBoundary-case likelihood fixes, bundled with the prior release's notes
  9. 2y agohydroloomInitial release completing the nhdplusTools migration
  10. 3y agomevGEV and GP distribution functions brought in-house to drop evd
  11. 4y agomevFour max-stable families, fixed parameters and threshold diagnostics

Frequently asked questions

What is the difference between hydroloom and mev?

Both compete on the same themes — r-package — within Analytics. hydroloom and mev are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is hydroloom better than mev?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hydroloom and mev are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to hydroloom?

Top hydroloom alternatives in Analytics are ranked by recent ship velocity. Browse the "hydroloom alternatives" section above for the current picks, or visit /alternatives/hydroloom for the full list with editorial commentary on each.

What are the best alternatives to mev?

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.