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invasimapr vs TidyDensity

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

invasimapr vs TidyDensity: at a glance

FeatureinvasimaprTidyDensity
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesinvasion ecology, species traits, biodiversity, research softwarestatistical-distributions, random-generation, parameter-estimation, tidyverse
Last editorial update6h ago51m ago
WebsiteVisit →Visit →

What is invasimapr?

invasimapr halved its install size and became citable; the science stayed put.

invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.

Read the full invasimapr trajectory →

What is TidyDensity?

A distribution catalogue that grows by one family at a time, and rarely breaks anything.

TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.

Read the full TidyDensity trajectory →

invasimapr vs TidyDensity: editorial side-by-side

I
invasimapr
ANALYTICS
0.0

invasimapr halved its install size and became citable; the science stayed put.

◆ Current state

invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.

◆ Where it's heading

The pressure is toward being installable and auditable rather than more capable — install slimmed from roughly 100 MB to 56 MB, R CMD check warnings and notes resolved, sp moved to Suggests, a Darwin Core-aligned data dictionary added, and a Zenodo concept DOI with CITATION.cff, codemeta.json and .zenodo.json. The package moves in lockstep with its B-Cubed sibling dissmapr, tagged within minutes of each other at both 0.1.0 and 0.2.1, which points at project-level standards deadlines rather than independent release decisions. Trait dispersion metrics and scenario exploration remain on the roadmap.

◆ Prediction

Standards compliance is now complete and the roadmap names functional trait dispersion metrics and scenario exploration tools, so the next release is the first that can plausibly be about invasion ecology rather than packaging.

T
TidyDensity
ANALYTICS
0.0

A distribution catalogue that grows by one family at a time, and rarely breaks anything.

◆ Current state

TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.

◆ Where it's heading

The package is filling out a matrix rather than changing shape — every new distribution gets the same four or five companion functions, so the surface grows predictably and the design does not. What variation exists comes from utilities that work across distributions: MCMC sampling, bootstrap helpers, time series conversion, distribution comparison. The two genuine breaking changes in this window were both internal reworks, moving generation onto data.table and rewriting quantile normalization for speed.

◆ Prediction

The established pattern of adding a distribution with its full helper set is the most likely continuation. Recent releases have been small, suggesting the catalogue is approaching the distributions its author considers worth covering.

Alternatives to invasimapr and TidyDensity

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 invasimapr or TidyDensity.

See all invasimapr alternatives → · See all TidyDensity alternatives →

Recent activity from invasimapr and TidyDensity

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

  1. 1mo agoinvasimaprVersion bump; notes identical to 0.2.0
  2. 1mo agoinvasimaprB-Cubed standards alignment; install slimmed to 56 MB
  3. 1mo agoinvasimaprinvasimapr v0.1.0: First citable release
  4. 11mo agoTidyDensityquantile_normalize rewritten, changing its output
  5. 1y agoTidyDensityDocumentation corrections for two distribution functions
  6. 2y agoTidyDensityZero-truncated distributions and AIC helpers added in bulk
  7. 2y agoTidyDensityMCMC sampling and quantile normalization join the utilities
  8. 2y agoTidyDensityGeneration moves to data.table; native pipe raises the R floor
  9. 2y agoTidyDensityDistributions convertible to time series objects

Frequently asked questions

What is the difference between invasimapr and TidyDensity?

They serve adjacent needs but don't currently overlap on shipped themes. invasimapr and TidyDensity 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 invasimapr better than TidyDensity?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. invasimapr and TidyDensity 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 invasimapr?

Top invasimapr alternatives in Analytics are ranked by recent ship velocity. Browse the "invasimapr alternatives" section above for the current picks, or visit /alternatives/invasimapr for the full list with editorial commentary on each.

What are the best alternatives to TidyDensity?

Top TidyDensity alternatives in Analytics are ranked by recent ship velocity. Browse the "TidyDensity alternatives" section above for the current picks, or visit /alternatives/tidydensity for the full list with editorial commentary on each.