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parglm vs ribd

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

parglm vs ribd: at a glance

Featureparglmribd
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesr, glm, parallel computing, c++statistical-genetics, pedigree-analysis, relatedness-coefficients, r-packages
Last editorial update13m ago2h ago
WebsiteVisit →Visit →

What is parglm?

Under a new maintainer, parglm traded raw speed work for glm parity and memory safety

parglm fits generalized linear models using parallel QR decomposition, targeting datasets where glm() is too slow. Tom Palmer took over maintenance at 0.1.8 in April 2026, and the package has released five times since — a burst of activity after a long quiet period. 0.2.0 in July 2026 is the first release to focus on correctness rather than throughput.

Read the full parglm trajectory →

What is ribd?

The pedsuite's coefficient engine: broadening what it computes, then making the plots publishable.

ribd computes relatedness coefficients from pedigrees, covering kinship, inbreeding, kappa, condensed and detailed identity coefficients, and two-locus versions of several of these, in autosomal and X-chromosomal form. The IBD triangle is now drawable in base graphics, ggplot2 or plotly, with an optional inset pedigree, and custom relationships can be placed on it. The most recent release is dominated by correctness work, fixing pair ordering and row alignment in coefficient tables and edge cases for pedigree lists, unrelated individuals and self-pairs.

Read the full ribd trajectory →

parglm vs ribd: editorial side-by-side

P
parglm
ANALYTICS
0.0

Under a new maintainer, parglm traded raw speed work for glm parity and memory safety

◆ Current state

parglm fits generalized linear models using parallel QR decomposition, targeting datasets where glm() is too slow. Tom Palmer took over maintenance at 0.1.8 in April 2026, and the package has released five times since — a burst of activity after a long quiet period. 0.2.0 in July 2026 is the first release to focus on correctness rather than throughput.

◆ Where it's heading

The arc runs from performance to trustworthiness. 0.1.9 was a large optimization release — deque-based task queues, fused memory passes, upper-triangle-only Fisher information, thread_local IDs — plus ecosystem integration with sandwich and gtsummary. 0.2.0 then fixed an out-of-bounds write triggered by small block_size values and a path where a non-finite working response could poison the QR decomposition, and brought response-type handling in line with glm().

◆ Prediction

With the memory-safety issues addressed and glm parity closed for binomial responses, further work is likely to extend family coverage or the benchmark suite rather than revisit the threading model. The C++17 requirement set at 0.1.8 gives room for more aggressive optimization if the maintainer returns to that.

R
ribd
ANALYTICS
2.5

The pedsuite's coefficient engine: broadening what it computes, then making the plots publishable.

◆ Current state

ribd computes relatedness coefficients from pedigrees, covering kinship, inbreeding, kappa, condensed and detailed identity coefficients, and two-locus versions of several of these, in autosomal and X-chromosomal form. The IBD triangle is now drawable in base graphics, ggplot2 or plotly, with an optional inset pedigree, and custom relationships can be placed on it. The most recent release is dominated by correctness work, fixing pair ordering and row alignment in coefficient tables and edge cases for pedigree lists, unrelated individuals and self-pairs.

◆ Where it's heading

The arc runs from generality to presentation to precision. Early releases replaced narrow functions with general ones, most visibly when gKinship() absorbed generalisedKinship() and identityCoefs() superseded the separate autosomal and X-chromosomal identity functions in favour of an Xchrom argument. The middle stretch turned the IBD triangle into a proper plotting surface across three graphics systems. The current phase reads as consolidation, with the newest release listing six bug fixes against four features, several of them alignment errors in output tables, which is where a coefficient library most needs to be exactly right.

◆ Prediction

The two new internal functions in the latest release, inbreedingContributions() and ancestralKinship(), are the kind of thing that surfaces publicly a release or two later, so expect them to become exported decomposition tools. The correctness push through pedigree lists and edge cases suggests the near-term focus stays on hardening rather than new coefficient families.

Alternatives to parglm and ribd

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 parglm or ribd.

See all parglm alternatives → · See all ribd alternatives →

Recent activity from parglm and ribd

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

  1. 12d agoribdCustom relationships on the IBD triangle; six alignment and edge-case fixes
  2. 1mo agoparglmglm-compatible response types plus out-of-bounds and QR safety fixes
  3. 2mo agoparglmBuild fixes for macOS SDK and thread pool includes
  4. 3mo agoparglmAdd missing <thread> include for older Apple SDKs
  5. 3mo agoparglmThreading overhaul, quasi families, and sandwich/gtsummary compatibility
  6. 3mo agoparglmNew maintainer takes over; C++17 now required
  7. 1y agoribdkappaIBD() can skip across-component pairs on large pedigrees
  8. 2y agoribdIBD triangle plots gain ggplot2 and plotly backends, plus inset pedigrees
  9. 3y agoribdTriangle line clipping, automatic plot margins, citation info
  10. 3y agoribdTwo-locus functions overhauled; twoLocusInbreeding and ELR added
  11. 4y agoribdIdentity coefficients unified behind identityCoefs() and an Xchrom argument

Frequently asked questions

What is the difference between parglm and ribd?

They serve adjacent needs but don't currently overlap on shipped themes. ribd is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is parglm better than ribd?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ribd is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to parglm?

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

What are the best alternatives to ribd?

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