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Comparison · Infra & APIs

ggpointless vs JointFPM

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

ggpointless vs JointFPM: at a glance

FeatureggpointlessJointFPM
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2-extensions, data-visualization, pictogram-charts, alpha-gradientssurvival-analysis, recurrent-events, parametric-models, api-stability
Last editorial update3h ago35m ago
WebsiteVisit →Visit →

What is ggpointless?

ggpointless keeps adding the ggplot2 layers nobody else bothered to write.

ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.

Read the full ggpointless trajectory →

What is JointFPM?

Recurrent-event modelling settles, with mean_no() promoted to stable.

JointFPM fits joint flexible parametric models for a recurrent event process alongside a competing terminal event, and predicts the mean number of events. The visible history runs from bug fixes on the earliest CRAN releases through standardization, integration options and a summary method, ending with mean_no() declared stable. Several changes arrived through outside pull requests.

Read the full JointFPM trajectory →

ggpointless vs JointFPM: editorial side-by-side

G
ggpointless
INFRA · APIS
0.0

ggpointless keeps adding the ggplot2 layers nobody else bothered to write.

◆ Current state

ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.

◆ Where it's heading

Two patterns are visible. Ideas get generalized rather than left as one-offs: geom_area_fade() in the previous release established alpha gradients via grid::linearGradient(), and the recent release spreads that treatment across paths, lines, steps, segments, curves and the three reference-line geoms, each with the same fade_direction and alpha_fade_to arguments. And each new geom is expected to survive real plots — the unit charts work under coord_equal, coord_polar, coord_radial, coord_flip and faceting, and geom_gridline reads positions from trained scales and inherits styling from the theme's panel grid. The package also tracks ggplot2 closely, requiring 4.0.0 and using make_constructor() and gg_par() internally, and it dropped its bundled datasets outright rather than maintain stale copies.

◆ Prediction

The fade treatment now covers most path-like geoms but not the area and ribbon family beyond geom_area_fade(), which is where the pattern has room left to run. The unit-cell charts arrive with a label helper and no fill or grouping variants, so those are the plausible next additions.

J
JointFPM
INFRA · APIS
0.0

Recurrent-event modelling settles, with mean_no() promoted to stable.

◆ Current state

JointFPM fits joint flexible parametric models for a recurrent event process alongside a competing terminal event, and predicts the mean number of events. The visible history runs from bug fixes on the earliest CRAN releases through standardization, integration options and a summary method, ending with mean_no() declared stable. Several changes arrived through outside pull requests.

◆ Where it's heading

The arc runs from a working estimator toward a usable one: input validation and error messages first, then control over the numerical integration, then a summary method and pass-through arguments to the underlying rstpm2 fit. The latest release adds no code so much as a stability commitment to a function users were already calling.

◆ Prediction

With mean_no() stable, the next work most likely targets the prediction and standardization paths rather than the model fit itself.

Alternatives to ggpointless and JointFPM

Other Infra & APIs 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 ggpointless or JointFPM.

See all ggpointless alternatives → · See all JointFPM alternatives →

Recent activity from ggpointless and JointFPM

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

  1. 3mo agoggpointlessPictogram unit charts, gridline layers and a family of fading geoms
  2. 5mo agoggpointlessFourier and arch geoms, area fades and glowing points
  3. 1y agoJointFPMmean_no() promoted to a stable interface
  4. 2y agoJointFPMsummary() method and control arguments passed to rstpm2
  5. 2y agoggpointlessgeom_catenary() draws a hanging chain
  6. 2y agoJointFPMGaussian quadrature option for the mean-events integration
  7. 2y agoJointFPMStandardized marginal estimates plus input validation
  8. 2y agoJointFPMBug fixes for differences between mean-event functions
  9. 3y agoggpointlessgeom_chaikin() adds corner-cutting path smoothing
  10. 4y agoggpointlessgeom_lexis() and the female_leaders dataset

Frequently asked questions

What is the difference between ggpointless and JointFPM?

They serve adjacent needs but don't currently overlap on shipped themes. ggpointless and JointFPM 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 ggpointless better than JointFPM?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggpointless and JointFPM 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 Infra & APIs products to evaluate alongside.

What are the best alternatives to ggpointless?

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

What are the best alternatives to JointFPM?

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