qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
Comparison · Analytics
quantities vs seriation
A side-by-side editorial comparison of quantities and seriation — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
quantities vs seriation: at a glance
What is quantities?
The glue package that makes R carry units and uncertainty through the same calculation.
quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.
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.
quantities vs seriation: editorial side-by-side
quantities
0.0ANALYTICS
The glue package that makes R carry units and uncertainty through the same calculation.
◆ Current state
quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.
◆ Where it's heading
The design settled with 0.2.0, which made uncertainty unit-aware and added correlation and covariance support for quantities objects. Since then the package behaves like the integration layer it is — releasing when units, errors, dplyr or ggplot2 shift underneath it rather than on its own schedule. Several releases consist only of test repairs against upstream changes.
◆ Prediction
Expect the next release to follow a units or errors change rather than introduce new behaviour of its own.
seriation
0.0ANALYTICS
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 quantities 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 quantities or seriation.
constants
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
austraits
The R client for AusTraits spends its releases chasing the dataset it reads.
ggdemetra
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
fossilsim
A fossil-record simulator that quietly grew a trait-evolution engine.
tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
See all quantities alternatives → · See all seriation alternatives →
Recent activity from quantities and seriation
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 0y agoseriationseriation 1.5.8 realigns linear criterion with Hubert and Schultz
- 1y agoquantitiesFixes covariance and correlation implementations
- 1y agoseriationseriation 1.5.7 adds BK_unconstrained, handles tiny inputs
- 1y agoseriationseriation 1.5.6 replaces FORTRAN BEA with C, modernizes allocation
- 2y agoquantitiesFaster data.frame methods
- 2y agoseriationseriation 1.5.5 digest: AOE method, rep parameter, MDS_angle fix
- 3y agoseriationseriation 1.5.1 refines pimage, permute and hmap
- 3y agoseriationseriation 1.5.0 adds seriate_best and parallel repeated search ⚡
- 3y agoquantitiesTest fixes for an upstream units change
- 3y agoquantitiesUncertainty becomes unit-aware; adds correlation support
- 5y agoquantitiesCompatibility fix for units 0.7-0
- 6y agoquantitiesFixes uncertainty propagation for offset unit conversions
Frequently asked questions
What is the difference between quantities and seriation?
Both compete on the same themes — r-package — within Analytics. quantities 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 quantities better than seriation?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. quantities 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 quantities?
Top quantities alternatives in Analytics are ranked by recent ship velocity. Browse the "quantities alternatives" section above for the current picks, or visit /alternatives/quantities 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.