nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Comparison · Analytics
trendseries vs vecvec
A side-by-side editorial comparison of trendseries and vecvec — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
trendseries vs vecvec: at a glance
What is trendseries?
A trend-extraction toolkit grows a full decomposition engine, seasonal components and all.
trendseries extracts trends from economic time series through two pipe-friendly functions, backed by an unusually broad method set — Hodrick-Prescott in one- and two-sided variants, Baxter-King, Christiano-Fitzgerald, Hamilton regression, Beveridge-Nelson, unobserved components, plus the moving average and smoothing family. The 1.4 release adds decomposition proper: an exported decompose_series() that splits a series into trend, seasonal, and remainder across five methods and guarantees the components add back to the original values.
What is vecvec?
A vector-of-vectors class swapped its object system mid-flight and came out faster.
vecvec provides an R class that holds multiple vectors as a single logical vector without copying them together, aimed at cases where concatenating would be wasteful. The 1.0.0 rewrite moved the class off vctrs onto S7 while keeping user-facing code working, and added matrix and array behaviour. Recent releases have concentrated on the details that decide whether the abstraction actually saves work: ALTREP vectors surviving intact, subassignment edge cases, and printing that does not materialise what it is describing.
trendseries vs vecvec: editorial side-by-side
trendseries
3.8ANALYTICS
A trend-extraction toolkit grows a full decomposition engine, seasonal components and all.
◆ Current state
trendseries extracts trends from economic time series through two pipe-friendly functions, backed by an unusually broad method set — Hodrick-Prescott in one- and two-sided variants, Baxter-King, Christiano-Fitzgerald, Hamilton regression, Beveridge-Nelson, unobserved components, plus the moving average and smoothing family. The 1.4 release adds decomposition proper: an exported decompose_series() that splits a series into trend, seasonal, and remainder across five methods and guarantees the components add back to the original values.
◆ Where it's heading
The package is moving from breadth of methods to rigour about what those methods produce. Recent work has been about defaults and guarantees rather than new filters: the unobserved components model now derives its signal-to-noise ratios from Hodrick-Prescott lambdas so the default output is economically interpretable, decomposition carries an exact additive identity, and a log transform gives a uniform multiplicative variant across every method. Naming is being tidied in the same spirit, with group_vars deprecated in favour of group_cols. Side-by-side method comparison — passing several methods and getting each one's components as separate columns — suggests an audience that treats method choice as a research question rather than a setting.
◆ Prediction
Expect the comparison and diagnostic side to keep developing, since the package now produces multiple decompositions of the same series and offers no ranking between them; the entries give no indication of new filters being queued.
vecvec
0.0ANALYTICS
A vector-of-vectors class swapped its object system mid-flight and came out faster.
◆ Current state
vecvec provides an R class that holds multiple vectors as a single logical vector without copying them together, aimed at cases where concatenating would be wasteful. The 1.0.0 rewrite moved the class off vctrs onto S7 while keeping user-facing code working, and added matrix and array behaviour. Recent releases have concentrated on the details that decide whether the abstraction actually saves work: ALTREP vectors surviving intact, subassignment edge cases, and printing that does not materialise what it is describing.
◆ Where it's heading
The arc runs from proving the idea to making it cheap. Early releases established constructors and vctrs dispatch; 1.0.0 rebuilt the internals on S7 with a smaller, faster representation and automatic flattening of adjacent compatible vectors; the two releases since have been about not defeating the point — an ALTREP vector flattened on construction or materialised by a print method gives back exactly the memory the class exists to save. Extensibility is the other visible thread, with custom ptype2 and cast methods now registrable and extension packages expected to subclass class_vecvec. The internal index structure is explicitly reserved for future change, so faster special-case representations look planned rather than incidental.
◆ Prediction
The reserved internal structure and the stated intent to accommodate faster variants point at specialised representations for particular vector types next; the entries do not indicate which cases are queued first.
Alternatives to trendseries and vecvec
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 trendseries or vecvec.
susier
Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs
UCell
A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next
detectseparation
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
brglm2
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
bayestools
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
See all trendseries alternatives → · See all vecvec alternatives →
Recent activity from trendseries and vecvec
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 15d agotrendseriesDecomposition becomes a first-class operation, five methods deep ⚡
- 1mo agovecvecExtension packages can register their own ptype and cast methods
- 1mo agovecvecALTREP vectors survive construction and printing intact
- 3mo agotrendseriesMulti-column trends and economically grounded UCM defaults
- 3mo agovecvecThe class is rebuilt on S7, with a new internal representation ⚡
- 4mo agovecvecMissing value handling fixed for is.na()
- 10mo agotrendseriesFirst production release with 21 trend extraction methods
- 11mo agovecvecArithmetic and per-vector apply arrive
- 11mo agovecvecFirst release: constructors and vctrs dispatch
Frequently asked questions
What is the difference between trendseries and vecvec?
Both compete on the same themes — r-package — within Analytics. trendseries is currently shipping more aggressively (velocity 3.8 vs 0.0), with 1 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 trendseries better than vecvec?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. trendseries is currently shipping more aggressively (velocity 3.8 vs 0.0), with 1 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 trendseries?
Top trendseries alternatives in Analytics are ranked by recent ship velocity. Browse the "trendseries alternatives" section above for the current picks, or visit /alternatives/trendseries for the full list with editorial commentary on each.
What are the best alternatives to vecvec?
Top vecvec alternatives in Analytics are ranked by recent ship velocity. Browse the "vecvec alternatives" section above for the current picks, or visit /alternatives/vecvec for the full list with editorial commentary on each.