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distributions3 vs ichimoku

A side-by-side editorial comparison of distributions3 and ichimoku — release velocity, themes, recent moves, and the top alternatives to consider.

distributions3 vs ichimoku: at a glance

Featuredistributions3ichimoku
SectorAnalyticsAnalytics
Velocity score6.30.0
Sparks · 30d10
Top themesr-package, probability-distributions, empirical-distributions, likelihood-inferencefinancial-charting, technical-analysis, dependency-reduction, oanda
Last editorial update1h ago4d ago
WebsiteVisit →Visit →

What is distributions3?

distributions3 0.3.0 adds sample-based distributions and likelihood derivatives

An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.

Read the full distributions3 trajectory →

What is ichimoku?

A cloud-chart package quietly swapping its dependencies for its maintainer's own libraries.

ichimoku implements Ichimoku Kinko Hyo cloud charts, strategy backtesting and an OANDA data interface for R. Recent releases are almost entirely plumbing: 1.5.7 drops RcppSimdJson in favor of secretbase for JSON parsing, following earlier releases that moved hashing to secretbase and raised the nanonext and mirai floors. The charting and strategy surface has been stable since the 1.5.0 line.

Read the full ichimoku trajectory →

distributions3 vs ichimoku: editorial side-by-side

D6.3

distributions3 0.3.0 adds sample-based distributions and likelihood derivatives

◆ Current state

An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.

◆ Where it's heading

Growth used to arrive as new distribution families contributed from outside - the extreme-value set, Erlang, later the Poisson binomial. This release changes the axis: alongside two new distributions it adds an inference layer (score, hessian) and a forecast-evaluation one (crps() methods against scoringRules), which are capabilities about distributions rather than more of them. Dependency weight is being cut at the same time, with ggplot2 demoted to Suggests and glue replaced by base R sprintf().

◆ Prediction

With numeric fallbacks and the derivative generics in place, expect analytic score() and hessian() methods to be filled in across more of the distribution catalogue. The constructor-default change is the likeliest source of follow-up fixes, since calls like Poisson() now return a length-zero distribution where they previously errored.

I
ichimoku
ANALYTICS
0.0

A cloud-chart package quietly swapping its dependencies for its maintainer's own libraries.

◆ Current state

ichimoku implements Ichimoku Kinko Hyo cloud charts, strategy backtesting and an OANDA data interface for R. Recent releases are almost entirely plumbing: 1.5.7 drops RcppSimdJson in favor of secretbase for JSON parsing, following earlier releases that moved hashing to secretbase and raised the nanonext and mirai floors. The charting and strategy surface has been stable since the 1.5.0 line.

◆ Where it's heading

The visible arc is consolidation onto the maintainer's own package family — secretbase for hashing and now JSON, nanonext and mirai for concurrency — which steadily removes third-party and Rcpp-based dependencies from the install chain. Feature work is sporadic and narrow when it comes: a faster POSIXct formatter exported as a utility, a multi-session option for the Shiny app, and a fix for asymmetric strategies that failed to emit a final entry signal.

◆ Prediction

Expect further dependency consolidation as the sibling packages gain capabilities, with ichimoku adopting them shortly after release rather than shipping new charting features.

Alternatives to distributions3 and ichimoku

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 distributions3 or ichimoku.

See all distributions3 alternatives → · See all ichimoku alternatives →

Recent activity from distributions3 and ichimoku

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

  1. 1h agodistributions3Empirical distributions, plus score and hessian generics
  2. 28d agodistributions3Maintenance moves to Achim Zeileis; moment calculations corrected
  3. 2mo agoichimokuJSON parsing moves from RcppSimdJson to secretbase
  4. 10mo agodistributions3ggplot2 compatibility for the plotting functions
  5. 1y agoichimokuFaster POSIXct formatting exported as a utility
  6. 1y agodistributions3Poisson binomial distribution, with a normal-approximation fallback
  7. 1y agoichimokuMultiple concurrent sessions in the OANDA Shiny app
  8. 2y agoichimokuAsymmetric strategies now emit their final entry signal
  9. 2y agoichimokusecretbase floor raised to 1.0.0
  10. 2y agoichimokuArchive verification reverts to SHA256
  11. 3y agodistributions3is_discrete and is_continuous generics, plus elementwise type-safety
  12. 4y agodistributions3Extreme-value family, Erlang, and a plotting generic

Frequently asked questions

What is the difference between distributions3 and ichimoku?

They serve adjacent needs but don't currently overlap on shipped themes. distributions3 is currently shipping more aggressively (velocity 6.3 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 distributions3 better than ichimoku?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributions3 is currently shipping more aggressively (velocity 6.3 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 distributions3?

Top distributions3 alternatives in Analytics are ranked by recent ship velocity. Browse the "distributions3 alternatives" section above for the current picks, or visit /alternatives/distributions3-r for the full list with editorial commentary on each.

What are the best alternatives to ichimoku?

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