fastml
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
Comparison · Analytics
randomwalk vs trendseries
A side-by-side editorial comparison of randomwalk and trendseries — release velocity, themes, recent moves, and the top alternatives to consider.
randomwalk vs trendseries: at a glance
What is randomwalk?
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
A random walk and fractal-growth simulation package whose entire visible history is about its browser deployment. Six releases in four weeks moved a Shinylive dashboard from a blank black page to a working app — WebAssembly mounted from GitHub releases, CORS resolved by same-origin serving, missing plotting dependencies installed in-browser, then an async version using crew workers with its own debug log. A correctness fix followed, adding termination-position validation so simulations stop producing isolated pixels, and the most recent release publishes the package itself as a webR binary repository.
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.
randomwalk vs trendseries: editorial side-by-side
randomwalk
0.0ANALYTICS
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
◆ Current state
A random walk and fractal-growth simulation package whose entire visible history is about its browser deployment. Six releases in four weeks moved a Shinylive dashboard from a blank black page to a working app — WebAssembly mounted from GitHub releases, CORS resolved by same-origin serving, missing plotting dependencies installed in-browser, then an async version using crew workers with its own debug log. A correctness fix followed, adding termination-position validation so simulations stop producing isolated pixels, and the most recent release publishes the package itself as a webR binary repository.
◆ Where it's heading
The package is being built as a browser artifact first and an R package second: the readme, the vignettes and the release notes all point at a hosted dashboard rather than at library(). The last release completes that by making the compiled WebAssembly build installable by anyone via webr::install(), which turns the deployment work into something reusable outside this project. Version numbers are unreliable here — v0.2.0 was published two weeks after v1.0.2 — so read the dates, not the tags.
◆ Prediction
With the webR repository published, the next work most likely moves back to the simulation itself, though the entries give no direct evidence of planned features.
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.
Alternatives to randomwalk and trendseries
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 randomwalk or trendseries.
abclass
abclass built out angle-based classifiers in 2022, then went quiet except for CRAN upkeep.
churon
churon is spending its entire release history getting a Rust ONNX binding through CRAN.
firatheme
firatheme woke up after four years and started fixing what ggplot2 changed underneath it.
bagyo
bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.
rainette
rainette rebuilt its Reinert clustering in 0.2.0, tuned it in 0.3.0, and has coasted since.
See all randomwalk alternatives → · See all trendseries alternatives →
Recent activity from randomwalk and trendseries
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 15d agotrendseriesDecomposition becomes a first-class operation, five methods deep ⚡
- 3mo agotrendseriesMulti-column trends and economically grounded UCM defaults
- 8mo agorandomwalkPackage published as an installable webR binary repository
- 8mo agorandomwalkTermination validation removes isolated pixels from simulations
- 8mo agorandomwalkAsync dashboard with crew workers running under WebR
- 9mo agorandomwalkBrowser dashboard working end to end
- 9mo agorandomwalkMissing plot dependency and parameter display fixed
- 9mo agorandomwalkDashboard mounts WebAssembly from GitHub releases
- 10mo agotrendseriesFirst production release with 21 trend extraction methods
Frequently asked questions
What is the difference between randomwalk and trendseries?
They serve adjacent needs but don't currently overlap on shipped themes. 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 randomwalk better than trendseries?
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 randomwalk?
Top randomwalk alternatives in Analytics are ranked by recent ship velocity. Browse the "randomwalk alternatives" section above for the current picks, or visit /alternatives/randomwalk for the full list with editorial commentary on each.
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.