Basedash
Basedash keeps pushing its data out of the workspace — now to people without accounts
A side-by-side editorial comparison of distributions3 and esquisse — release velocity, themes, recent moves, and the top alternatives to consider.
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.
esquisse's 1.0 turned a point-and-click addin into embeddable Shiny modules.
The visible history covers the 1.0 line only. 1.0.0 is the substantial one: modules for importing data (via datamods) and exporting plots, a `ggplot_output()` / `render_ggplot()` pair, manual colour palettes, aesthetic parameter selection, more export formats including pptx, and typography controls. 1.0.1 and 1.0.2 are corrective — sf object handling, package-sourced data, disabled-panel label controls, and an `output_format` argument on the save modal.
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.
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().
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.
The visible history covers the 1.0 line only. 1.0.0 is the substantial one: modules for importing data (via datamods) and exporting plots, a `ggplot_output()` / `render_ggplot()` pair, manual colour palettes, aesthetic parameter selection, more export formats including pptx, and typography controls. 1.0.1 and 1.0.2 are corrective — sf object handling, package-sourced data, disabled-panel label controls, and an `output_format` argument on the save modal.
The arc runs from a self-contained RStudio addin toward a component library other people build with: once plot rendering and export exist as Shiny modules, esquisse's ggplot builder can be dropped inside someone else's app rather than only launched beside RStudio. The two follow-up releases are consolidation on that surface rather than expansion of it.
Further work most likely lands on the module API and export coverage, since that is where 1.0.0 put the new surface and where 1.0.2 already returned. The entries do not indicate anything about cadence beyond this line.
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 esquisse.
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See all distributions3 alternatives → · See all esquisse alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
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.
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.
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.
Top esquisse alternatives in Analytics are ranked by recent ship velocity. Browse the "esquisse alternatives" section above for the current picks, or visit /alternatives/esquisse for the full list with editorial commentary on each.