randomwalk
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
Comparison · Analytics
simStateSpace vs trendseries
A side-by-side editorial comparison of simStateSpace and trendseries — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
simStateSpace vs trendseries: at a glance
What is simStateSpace?
State-space data simulation for R, filled in one function at a time
simStateSpace generates data from state-space models — discrete-time SSM and VAR, continuous-time linear SDE and Ornstein-Uhlenbeck — for use in simulation studies of longitudinal and intensive repeated-measures designs. Recent releases add moment and intercept helpers rather than new model families: SimMVN(), the LinSDE intercept functions, and consolidation of the four separate parameter-simulation functions into one. Release notes are terse, marked Patch, and typically name one or two functions.
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.
simStateSpace vs trendseries: editorial side-by-side
simStateSpace
0.0ANALYTICS
State-space data simulation for R, filled in one function at a time
◆ Current state
simStateSpace generates data from state-space models — discrete-time SSM and VAR, continuous-time linear SDE and Ornstein-Uhlenbeck — for use in simulation studies of longitudinal and intensive repeated-measures designs. Recent releases add moment and intercept helpers rather than new model families: SimMVN(), the LinSDE intercept functions, and consolidation of the four separate parameter-simulation functions into one. Release notes are terse, marked Patch, and typically name one or two functions.
◆ Where it's heading
The package is being filled in methodically toward completeness across its four model families — whatever exists for the SSM side eventually appears for LinSDE and back again, as SSMInterceptEta/SSMInterceptY in 1.2.15 were followed by their LinSDE counterparts in 1.2.16. The other visible move was outward: bootstrap components were split into a separate bootStateSpace package, keeping this one to simulation alone. It sits in the same author's cluster of state-space and mediation packages, whose published methods papers the releases cite.
◆ Prediction
Expect the pattern to continue — small patch releases adding the missing counterpart function for a model family already served, with any larger capability likely spun out into its own package as bootstrapping was.
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 simStateSpace 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 simStateSpace or trendseries.
fastml
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
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.
See all simStateSpace alternatives → · See all trendseries alternatives →
Recent activity from simStateSpace 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
- 4mo agosimStateSpaceLinSDE intercept helpers added; parameter simulators consolidated
- 6mo agosimStateSpaceSSM intercept functions added
- 10mo agosimStateSpacesimStateSpace 1.2.12
- 10mo agotrendseriesFirst production release with 21 trend extraction methods
- 1y agosimStateSpaceLinSDECov() and LinSDEMean() added
- 1y agosimStateSpaceBootstrap components split into bootStateSpace
- 1y agosimStateSpaceParametric bootstrap functions across all four model families
Frequently asked questions
What is the difference between simStateSpace and trendseries?
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 simStateSpace 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 simStateSpace?
Top simStateSpace alternatives in Analytics are ranked by recent ship velocity. Browse the "simStateSpace alternatives" section above for the current picks, or visit /alternatives/simstatespace 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.