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gghighlight vs mev

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

Shared themes:r-package

gghighlight vs mev: at a glance

Featuregghighlightmev
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, data-visualisation, ggplot-extension, upstream-compatextreme-value-theory, threshold-selection, statistical-estimation, api-redesign
Last editorial update1h ago2h ago
WebsiteVisit →Visit →

What is gghighlight?

A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.

gghighlight adds one verb to ggplot2: highlight the series matching a predicate and grey out the rest, with unhighlighted_params controlling how the shadowed layer renders and calculate_per_facet deciding whether the predicate evaluates within facets. The API settled at 0.2.0; the 0.5.0 release supports ggplot2 v4.0 including its ink and paper theme elements, and finally deletes gghighlight_point() and gghighlight_line().

Read the full gghighlight 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 →

gghighlight vs mev: editorial side-by-side

G
gghighlight
ANALYTICS
0.0

A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.

◆ Current state

gghighlight adds one verb to ggplot2: highlight the series matching a predicate and grey out the rest, with unhighlighted_params controlling how the shadowed layer renders and calculate_per_facet deciding whether the predicate evaluates within facets. The API settled at 0.2.0; the 0.5.0 release supports ggplot2 v4.0 including its ink and paper theme elements, and finally deletes gghighlight_point() and gghighlight_line().

◆ Where it's heading

Two threads run through the history. One is a slow deprecation, from soft-deprecating the geom-specific functions at 0.1.0, to defunct at 0.3.0, to removed at 0.5.0 — a five-year removal cycle. The other is compatibility work: purrr 1.0.0, dplyr's across() deprecation, ggplot2 3.4.0, then 4.0. Genuine feature additions are rare and small, with line_label_type at 0.4.0 the last one. Note that 0.3.2's notes restate 0.3.1's n() item, so adjacent tags here overlap rather than each describing distinct work.

◆ Prediction

The next release most likely absorbs further ggplot2 4.x changes, given that is what triggered the last three. Nothing in the entries points to a new highlighting capability.

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 gghighlight 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 gghighlight or mev.

See all gghighlight alternatives → · See all mev alternatives →

Recent activity from gghighlight and mev

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

  1. 9mo agomevTwo more threshold-selection routines slot into the new scheme
  2. 9mo agomevThreshold, stability and dependence functions regrouped under prefixes
  3. 1y agogghighlightggplot2 v4.0 support; geom-specific functions removed
  4. 2y agomevBoundary-case likelihood fixes, bundled with the prior release's notes
  5. 2y agogghighlightTest expectations updated for upcoming ggplot2
  6. 3y agomevGEV and GP distribution functions brought in-house to drop evd
  7. 3y agogghighlightline_label_type adds geomtextpath and second-axis labelling
  8. 4y agogghighlightDeprecated dplyr::across() usage removed
  9. 4y agomevFour max-stable families, fixed parameters and threshold diagnostics
  10. 5y agogghighlightExplicit NULL in unhighlighted_params preserved; aesthetic name clash fixed
  11. 5y agogghighlightDiscrete-scale labels and n() predicates

Frequently asked questions

What is the difference between gghighlight and mev?

Both compete on the same themes — r-package — within Analytics. gghighlight 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 gghighlight better than mev?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. gghighlight 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 gghighlight?

Top gghighlight alternatives in Analytics are ranked by recent ship velocity. Browse the "gghighlight alternatives" section above for the current picks, or visit /alternatives/gghighlight 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.