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Comparison · Analytics

gghighlight vs intsurv

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

Shared themes:r-package

gghighlight vs intsurv: at a glance

Featuregghighlightintsurv
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, data-visualisation, ggplot-extension, upstream-compatsurvival-analysis, cure-models, censored-data, regularization
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 intsurv?

A Cox cure-rate model package woke up after four years to simplify its own interface.

intsurv fits Cox cure rate models for right-censored survival data where event status may be uncertain — the case where you cannot tell whether a subject experienced the event or was never susceptible to it. The core has been stable since 2019: cox_cure() and its regularized counterpart cox_cure_net(), plus a weighted concordance index and a data simulator. After more than four years without a release, version 0.3.0 arrived in September 2025 and restructured how those two functions are configured rather than adding capability.

Read the full intsurv trajectory →

gghighlight vs intsurv: 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.

I
intsurv
ANALYTICS
0.0

A Cox cure-rate model package woke up after four years to simplify its own interface.

◆ Current state

intsurv fits Cox cure rate models for right-censored survival data where event status may be uncertain — the case where you cannot tell whether a subject experienced the event or was never susceptible to it. The core has been stable since 2019: cox_cure() and its regularized counterpart cox_cure_net(), plus a weighted concordance index and a data simulator. After more than four years without a release, version 0.3.0 arrived in September 2025 and restructured how those two functions are configured rather than adding capability.

◆ Where it's heading

The package has reached the point where the methods are settled and the remaining work is ergonomics. Moving control parameters, M-step settings and penalty specification into cox_cure.control(), cox_cure.mstep() and cox_cure_net.penalty() follows the established R convention of separating tuning from the model formula, and it arrives long after the arguments accumulated. The C++ headers were placed in inst/include as early as 2019 so other packages could link against them, which suggests the implementation was always intended to be reused.

◆ Prediction

The gap between 0.2.2 and 0.3.0 makes cadence a poor basis for prediction. What the entries do support is that the interface rework is unfinished business rather than a prelude to new methods, so consolidation around the new helper functions is the likelier next step.

Alternatives to gghighlight and intsurv

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 intsurv.

See all gghighlight alternatives → · See all intsurv alternatives →

Recent activity from gghighlight and intsurv

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

  1. 10mo agointsurvModel configuration moves into dedicated control functions
  2. 1y agogghighlightggplot2 v4.0 support; geom-specific functions removed
  3. 2y agogghighlightTest expectations updated for upcoming ggplot2
  4. 3y agogghighlightline_label_type adds geomtextpath and second-axis labelling
  5. 4y agogghighlightDeprecated dplyr::across() usage removed
  6. 5y agogghighlightExplicit NULL in unhighlighted_params preserved; aesthetic name clash fixed
  7. 5y agointsurvCross-validated model selection and offset terms added
  8. 5y agogghighlightDiscrete-scale labels and n() predicates
  9. 6y agointsurvC++ headers relocated so other packages can link them
  10. 7y agointsurvCox cure models for uncertain event status arrive
  11. 7y agointsurvParameter initialization methods added to the alpha
  12. 7y agointsurvAlpha cut for paper submission and simulation reproducibility

Frequently asked questions

What is the difference between gghighlight and intsurv?

Both compete on the same themes — r-package — within Analytics. gghighlight and intsurv 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 intsurv?

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

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