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Comparison · Analytics

epikit vs seriation

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

Shared themes:r-package

epikit vs seriation: at a glance

Featureepikitseriation
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesepidemiology, field-data, date-handling, r-packageseriation, matrix-reordering, optimization, clustering
Last editorial update1h ago48m ago
WebsiteVisit →Visit →

What is epikit?

epikit narrows to field-epidemiology helpers, handing proportions to a sibling package

epikit is a set of small helpers for applied epidemiology in R — age categorisation, date reconstruction from partial records, and related field-data chores, developed in the R4Epis orbit. Version 0.2.0 moved the proportion functions out to epitabulate, improved how find_date_cause(), find_start_date() and find_end_date() handle dates falling outside the period, and added a floor argument to age_categories() so the lowest band reads as under one rather than zero to zero.

Read the full epikit trajectory →

What is seriation?

seriation stopped shipping algorithms and started shipping a way to pick between them.

seriation finds meaningful orderings for matrices, distance objects and dendrograms, and carries a large registry of methods from classic combinatorial criteria to t-SNE and UMAP embeddings. The 1.5.0 release added a layer above that registry — seriate_best(), seriate_rep() and seriate_improve() — which run randomized methods repeatedly, in parallel, and keep the best result. Recent work is definitional and numeric rather than additive: 1.5.8 corrects the linear seriation criterion to match Hubert and Schultz's original 1976 definition.

Read the full seriation trajectory →

epikit vs seriation: editorial side-by-side

E
epikit
ANALYTICS
0.0

epikit narrows to field-epidemiology helpers, handing proportions to a sibling package

◆ Current state

epikit is a set of small helpers for applied epidemiology in R — age categorisation, date reconstruction from partial records, and related field-data chores, developed in the R4Epis orbit. Version 0.2.0 moved the proportion functions out to epitabulate, improved how find_date_cause(), find_start_date() and find_end_date() handle dates falling outside the period, and added a floor argument to age_categories() so the lowest band reads as under one rather than zero to zero.

◆ Where it's heading

The package is being scoped down rather than built out. The 0.1.3 restructuring and the 0.2.0 handover of proportions to epitabulate are the same move made twice: push functionality into the package where it belongs and keep epikit to the toolkit that field epidemiologists reach for directly. The rest of the history is dependency compatibility work against dplyr and tibble.

◆ Prediction

With proportions gone and dependencies trimmed, the remaining functions cluster tightly around dates and age bands, so further refinement of the date-reconstruction helpers is more likely than new capability areas.

S
seriation
ANALYTICS
0.0

seriation stopped shipping algorithms and started shipping a way to pick between them.

◆ Current state

seriation finds meaningful orderings for matrices, distance objects and dendrograms, and carries a large registry of methods from classic combinatorial criteria to t-SNE and UMAP embeddings. The 1.5.0 release added a layer above that registry — seriate_best(), seriate_rep() and seriate_improve() — which run randomized methods repeatedly, in parallel, and keep the best result. Recent work is definitional and numeric rather than additive: 1.5.8 corrects the linear seriation criterion to match Hubert and Schultz's original 1976 definition.

◆ Where it's heading

The package has shifted from breadth to judgment. Through 1.3.x the additions were new methods; from 1.5.0 the registry started carrying metadata about the methods — whether they are randomized, what criterion they optimize — so the package could choose and evaluate on the user's behalf. The 1.5.6 replacement of FORTRAN with C for BEA and ME points the same way, reducing the legacy surface underneath that machinery.

◆ Prediction

Further criterion audits are the likeliest next move, since 1.5.8 shows a published definition being reconciled against the implementation and the registry now records what each method optimizes. Expect corrections rather than new seriation algorithms.

Alternatives to epikit and seriation

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 epikit or seriation.

See all epikit alternatives → · See all seriation alternatives →

Recent activity from epikit and seriation

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

  1. 9mo agoepikitProportion functions moved to epitabulate; date helpers warn correctly
  2. 0y agoseriationseriation 1.5.8 realigns linear criterion with Hubert and Schultz
  3. 1y agoseriationseriation 1.5.7 adds BK_unconstrained, handles tiny inputs
  4. 1y agoseriationseriation 1.5.6 replaces FORTRAN BEA with C, modernizes allocation
  5. 2y agoseriationseriation 1.5.5 digest: AOE method, rep parameter, MDS_angle fix
  6. 3y agoseriationseriation 1.5.1 refines pimage, permute and hmap
  7. 3y agoseriationseriation 1.5.0 adds seriate_best and parallel repeated search
  8. 3y agoepikitFunctions rearranged across sibling packages
  9. 5y agoepikitRaise dplyr and tibble minimums; move CI to GitHub Actions
  10. 5y agoepikitCompatibility release for dplyr 1.0.0
  11. 6y agoepikitFirst CRAN release

Frequently asked questions

What is the difference between epikit and seriation?

Both compete on the same themes — r-package — within Analytics. epikit and seriation 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 epikit better than seriation?

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

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

What are the best alternatives to seriation?

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