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forecasting vs TidyDensity

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

forecasting vs TidyDensity: at a glance

FeatureforecastingTidyDensity
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesforecasting, epidemiology, reproducibility, vignettesstatistical-distributions, random-generation, parameter-estimation, tidyverse
Last editorial update7h ago1h ago
WebsiteVisit →Visit →

What is forecasting?

HIDDA.forecasting is a book chapter's reproducibility artifact, not a package under development.

HIDDA.forecasting accompanies a book chapter on forecasting infectious disease counts; its vignettes reproduce the results presented there using arima, prophet, glarma, hhh4contacts and scoringRules. The 1.0.0 release states this outright — it is the version used for the chapter, pinned to CRAN package versions as of July 2018. Every release since has been a vignette rebuild against newer R and dependency versions.

Read the full forecasting 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 →

forecasting vs TidyDensity: editorial side-by-side

F
forecasting
ANALYTICS
0.0

HIDDA.forecasting is a book chapter's reproducibility artifact, not a package under development.

◆ Current state

HIDDA.forecasting accompanies a book chapter on forecasting infectious disease counts; its vignettes reproduce the results presented there using arima, prophet, glarma, hhh4contacts and scoringRules. The 1.0.0 release states this outright — it is the version used for the chapter, pinned to CRAN package versions as of July 2018. Every release since has been a vignette rebuild against newer R and dependency versions.

◆ Where it's heading

The release pattern is maintenance on an eight-year cadence dictated entirely by the surrounding ecosystem: 1.1.1 rebuilt under R 4.0.4, 1.1.2 under R 4.3.2, 1.1.3 under R 4.6.1, each reporting whether the numbers moved. They mostly have not — the recurring note is minor numerical differences confined to the prophet forecasts in vignette('CHILI_prophet'). The only substantive change in the visible history is 1.1.0's methodological tidy-up of the scoring comparisons.

◆ Prediction

Nothing in these entries points to new functionality; the next release is most likely another vignette rebuild whenever a dependency change or a CRAN check failure forces one.

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 forecasting 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 forecasting or TidyDensity.

See all forecasting alternatives → · See all TidyDensity alternatives →

Recent activity from forecasting and TidyDensity

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

  1. 1mo agoforecastingVignettes rebuilt under R 4.6.1
  2. 11mo agoTidyDensityquantile_normalize rewritten, changing its output
  3. 1y agoTidyDensityDocumentation corrections for two distribution functions
  4. 2y agoTidyDensityZero-truncated distributions and AIC helpers added in bulk
  5. 2y agoTidyDensityMCMC sampling and quantile normalization join the utilities
  6. 2y agoTidyDensityGeneration moves to data.table; native pipe raises the R floor
  7. 2y agoforecastingVignettes rebuilt under R 4.3.2
  8. 2y agoTidyDensityDistributions convertible to time series objects
  9. 5y agoforecastingVignettes rebuilt under R 4.0.4
  10. 7y agoforecastingStandard PIT and discretized log-normal scoring
  11. 7y agoforecastingThe version used for the book chapter, with pinned dependencies

Frequently asked questions

What is the difference between forecasting and TidyDensity?

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

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

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