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ggmapinset vs intsurv

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

ggmapinset vs intsurv: at a glance

Featureggmapinsetintsurv
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, geospatial, inset-maps, extension-apisurvival-analysis, cure-models, censored-data, regularization
Last editorial update2h ago45m ago
WebsiteVisit →Visit →

What is ggmapinset?

A ggplot2 inset-map extension that is now infrastructure for other packages

ggmapinset adds magnified inset panels to ggplot2 sf maps, handling the coordinate transformation, the inset frame and the sf-related stat layers that have to follow it. The 0.5.0 release is aimed less at end users than at extension authors: coerce_centre() is a new extension point required by sibling package ggautomap, and the inset parameter drops NA in favour of waiver() as its default. It comes from cidm-ph, alongside nswgeo.

Read the full ggmapinset 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 →

ggmapinset vs intsurv: editorial side-by-side

G
ggmapinset
ANALYTICS
0.0

A ggplot2 inset-map extension that is now infrastructure for other packages

◆ Current state

ggmapinset adds magnified inset panels to ggplot2 sf maps, handling the coordinate transformation, the inset frame and the sf-related stat layers that have to follow it. The 0.5.0 release is aimed less at end users than at extension authors: coerce_centre() is a new extension point required by sibling package ggautomap, and the inset parameter drops NA in favour of waiver() as its default. It comes from cidm-ph, alongside nswgeo.

◆ Where it's heading

The package has moved steadily from feature to foundation. 0.3.0 replaced confusing parameter names and rebuilt everything on stat_sf_inset() so coordinate limits stayed correct, then exposed transform_to_inset() explicitly for extension developers. 0.4.0 generalised inset shapes beyond circles to rectangles and arbitrary sf geometries. 0.5.0 continues in that direction, changing defaults in ways that require downstream extensions to adapt — the cost of being depended upon.

◆ Prediction

Expect further extension points driven by what ggautomap and the other cidm-ph mapping packages need, with the user-facing inset API staying largely settled after the shape generalisation.

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 ggmapinset 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 ggmapinset or intsurv.

See all ggmapinset alternatives → · See all intsurv alternatives →

Recent activity from ggmapinset and intsurv

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

  1. 4mo agoggmapinsetNew extension point for ggautomap; waiver() replaces NA
  2. 10mo agointsurvModel configuration moves into dedicated control functions
  3. 1y agoggmapinsetRectangular and arbitrary sf inset shapes
  4. 3y agoggmapinsetRebuilt on stat_sf_inset() with corrected coordinate limits
  5. 5y agointsurvCross-validated model selection and offset terms added
  6. 6y agointsurvC++ headers relocated so other packages can link them
  7. 7y agointsurvCox cure models for uncertain event status arrive
  8. 7y agointsurvParameter initialization methods added to the alpha
  9. 7y agointsurvAlpha cut for paper submission and simulation reproducibility

Frequently asked questions

What is the difference between ggmapinset and intsurv?

They serve adjacent needs but don't currently overlap on shipped themes. ggmapinset 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 ggmapinset better than intsurv?

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

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