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Comparison · Infra & APIs

L1centrality vs profileCI

A side-by-side editorial comparison of L1centrality and profileCI — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

L1centrality vs profileCI: at a glance

FeatureL1centralityprofileCI
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesgraph-analysis, centrality, r-package, visualizationprofile-likelihood, confidence-intervals, statistics, numerical-robustness
Last editorial update54m ago2d ago
WebsiteVisit →Visit →

What is L1centrality?

A graph-centrality package that spent 2026 making its existing measures usable at scale, then went quiet.

L1centrality implements L1 centrality and prestige for graphs, including group, local, and neighbourhood variants plus MDS-based visualization. The measure set has been stable since 0.3.0; the work since has gone into interfaces around it — S3 classes with print and summary methods, plot methods for every result class, and in 0.5.0 both multi-group evaluation and multicore computation for the local variant. The two releases since have been a warning-message pass and a typo pass.

Read the full L1centrality trajectory →

What is profileCI?

Profile-likelihood confidence intervals for any fitted model, in a feed that publishes out of order.

profileCI computes confidence intervals from the profile log-likelihood for user-supplied fitted models, generalising what confint.glm does for GLMs to any model object exposing a log-likelihood. The releases handle the awkward cases that make profiling fail in practice: infinite limits when the profile never drops below the interval threshold, bounded profiling ranges, and interpolation that breaks down near the limits. Only convex log-likelihoods are supported, so disjoint intervals are out of scope by design.

Read the full profileCI trajectory →

L1centrality vs profileCI: editorial side-by-side

L
L1centrality
INFRA · APIS
0.0

A graph-centrality package that spent 2026 making its existing measures usable at scale, then went quiet.

◆ Current state

L1centrality implements L1 centrality and prestige for graphs, including group, local, and neighbourhood variants plus MDS-based visualization. The measure set has been stable since 0.3.0; the work since has gone into interfaces around it — S3 classes with print and summary methods, plot methods for every result class, and in 0.5.0 both multi-group evaluation and multicore computation for the local variant. The two releases since have been a warning-message pass and a typo pass.

◆ Where it's heading

The package has moved from defining measures to operationalizing them. 0.5.0 was the inflection: parallel local computation and list-valued group input both target users running these measures over many vertex sets or large graphs rather than illustrating them on one. The same release renamed weight_transform and eta to edge_weight_transform and vertex_weight, and added an explicit message when a distance matrix is received — the signature of a maintainer fielding the same misuse repeatedly.

◆ Prediction

The last two releases carry no functional change, so the near-term path is maintenance rather than new measures; a 0.6.0 would most likely extend parallelism beyond L1centLOC to the other computationally heavy variants.

P
profileCI
INFRA · APIS
0.0

Profile-likelihood confidence intervals for any fitted model, in a feed that publishes out of order.

◆ Current state

profileCI computes confidence intervals from the profile log-likelihood for user-supplied fitted models, generalising what confint.glm does for GLMs to any model object exposing a log-likelihood. The releases handle the awkward cases that make profiling fail in practice: infinite limits when the profile never drops below the interval threshold, bounded profiling ranges, and interpolation that breaks down near the limits. Only convex log-likelihoods are supported, so disjoint intervals are out of scope by design.

◆ Where it's heading

Work is concentrated on numerical reliability rather than scope: 1.1.1 replaced quadratic with monotonic cubic spline interpolation because the quadratic form could fail, and corrected parameter values stored near the confidence limits. The feed publishes these out of order, with the v1.0.0 entry stamped six months after v1.1.0 and carrying the package's full description rather than a changelog, so release order should be read from the version numbers rather than the dates. The same maintainer's revdbayes has been in pure maintenance across this period, which places profileCI as the more active project.

◆ Prediction

Expect further robustness work at the profiling limits and more logLikFn methods for common model classes, following the nls method added in 1.1.0.

Alternatives to L1centrality and profileCI

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 L1centrality or profileCI.

See all L1centrality alternatives → · See all profileCI alternatives →

Recent activity from L1centrality and profileCI

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

  1. 1mo agoL1centralityTypo fixes only
  2. 3mo agoL1centralityWarning message wording updated
  3. 3mo agoL1centralityMulti-group prominence and multicore local centrality
  4. 6mo agoprofileCICubic spline interpolation replaces a quadratic that could fail
  5. 7mo agoprofileCICRAN 1.0.0 release of profile-likelihood interval computation
  6. 9mo agoL1centralityPlot methods for every result class, plus edge-weight transforms
  7. 1y agoprofileCIInfinite limits and bounded profiling ranges handled
  8. 1y agoL1centralityHandles unnamed vertices; quantile type pinned
  9. 1y agoL1centralityS3 classes for all results, plus a Gini coefficient

Frequently asked questions

What is the difference between L1centrality and profileCI?

Both compete on the same themes — r-package — within Infra & APIs. L1centrality and profileCI 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 L1centrality better than profileCI?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. L1centrality and profileCI 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 L1centrality?

Top L1centrality alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "L1centrality alternatives" section above for the current picks, or visit /alternatives/l1centrality for the full list with editorial commentary on each.

What are the best alternatives to profileCI?

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