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simlandr vs trendseries

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

Shared themes:r-package

simlandr vs trendseries: at a glance

Featuresimlandrtrendseries
SectorAnalyticsAnalytics
Velocity score0.03.8
Sparks · 30d01
Top themesr-package, dynamical-systems, visualization, api-consolidationtime-series, econometrics, r-package, seasonal-decomposition
Last editorial update50m ago6h ago
WebsiteVisit →Visit →

What is simlandr?

Potential landscape tooling settling onto standard R generics after two rounds of renaming.

simlandr builds potential landscape plots from simulations of dynamic systems, with barrier-height calculations and batch simulation grids. Its three substantive releases are all consolidation: parameters renamed, functions renamed, defaults removed. By 0.3.0 the bespoke accessors had been replaced by ggplot2's autolayer() and base summary(), and the package carried print, summary, and plot methods for its own classes.

Read the full simlandr trajectory →

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.

Read the full trendseries trajectory →

simlandr vs trendseries: editorial side-by-side

S
simlandr
ANALYTICS
0.0

Potential landscape tooling settling onto standard R generics after two rounds of renaming.

◆ Current state

simlandr builds potential landscape plots from simulations of dynamic systems, with barrier-height calculations and batch simulation grids. Its three substantive releases are all consolidation: parameters renamed, functions renamed, defaults removed. By 0.3.0 the bespoke accessors had been replaced by ggplot2's autolayer() and base summary(), and the package carried print, summary, and plot methods for its own classes.

◆ Where it's heading

Every release trades a package-specific name for a conventional one - var and par became arg and ele, get_geom() became an autolayer() method, get_barrier_height() became a summary() method, hash_big.matrix became hash_big_matrix. The one methodological change, an adjusted minimal energy path algorithm, arrived inside a release otherwise full of renames. Removing default values for barrier calculation because they were often unsuitable reads as the maintainer deciding the defaults were doing harm.

◆ Prediction

The feed stops at 0.3.0 in late 2022, mid-consolidation; these entries give no indication of what followed, if anything did.

T
trendseries
ANALYTICS
3.8

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 simlandr 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 simlandr or trendseries.

See all simlandr alternatives → · See all trendseries alternatives →

Recent activity from simlandr and trendseries

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

  1. 15d agotrendseriesDecomposition becomes a first-class operation, five methods deep
  2. 3mo agotrendseriesMulti-column trends and economically grounded UCM defaults
  3. 10mo agotrendseriesFirst production release with 21 trend extraction methods
  4. 3y agosimlandrAccessors replaced by autolayer and summary methods
  5. 3y agosimlandrroxygen2 updated for HTML5 compatibility
  6. 4y agosimlandrBatch simulation arguments renamed; energy path algorithm adjusted
  7. 4y agosimlandrManual improved and a test function added
  8. 5y agosimlandrPackage cleaned for CRAN compatibility

Frequently asked questions

What is the difference between simlandr 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 simlandr 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 simlandr?

Top simlandr alternatives in Analytics are ranked by recent ship velocity. Browse the "simlandr alternatives" section above for the current picks, or visit /alternatives/simlandr 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.