rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
ggstatsplot vs mizer
A side-by-side editorial comparison of ggstatsplot and mizer — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
ggstatsplot vs mizer: at a glance
What is ggstatsplot?
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
What is mizer?
After two and a half years dormant, mizer shipped three major versions in seven weeks.
The size-spectrum fish modelling package sat at 2.5.0 from December 2023 until June 2026, then released 3.0.0, 3.1.0 and 3.2.0 in the space of seven weeks. The three releases divide cleanly: 3.0.0 added biological realism through a diffusion term in the McKendrick-von Foerster equation, 3.1.0 added an opt-in second-order numerical scheme in size, and 3.2.0 rebuilt how species and resource parameters are set. Backward compatibility is handled carefully throughout — the experimental scheme is off by default and the first-order path is byte-identical to previous versions.
ggstatsplot vs mizer: editorial side-by-side
ggstatsplot
0.0ANALYTICS
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
◆ Current state
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
◆ Where it's heading
The architecture explains the cadence. With statistics living in statsExpressions, ggstatsplot's own releases are mostly the tax of sitting on top of a fast-moving plotting and tidyverse stack — five of the six most recent entries change nothing a user would notice. When substantive work does arrive it clusters in the plotting layer's coverage of test families, as in 1.0.0's one-sample goodness-of-fit support and pairwise contingency analyses. The maintainer is also visibly deliberate about scope, having removed the normality-curve overlay in 0.12.4 for being unrelated to the analysis in question.
◆ Prediction
Expect continued parity work across the plot family — features that exist in one function being extended to its siblings, as goodness-of-fit support moved from ggpiestats to ggbarstats — punctuated by maintenance releases tracking ggplot2 and easystats.
mizer
5.0ANALYTICS
After two and a half years dormant, mizer shipped three major versions in seven weeks.
◆ Current state
The size-spectrum fish modelling package sat at 2.5.0 from December 2023 until June 2026, then released 3.0.0, 3.1.0 and 3.2.0 in the space of seven weeks. The three releases divide cleanly: 3.0.0 added biological realism through a diffusion term in the McKendrick-von Foerster equation, 3.1.0 added an opt-in second-order numerical scheme in size, and 3.2.0 rebuilt how species and resource parameters are set. Backward compatibility is handled carefully throughout — the experimental scheme is off by default and the first-order path is byte-identical to previous versions.
◆ Where it's heading
Two threads run through the 3.x line. The first is numerical: diffusion, then higher-order accuracy in both size and time, with explicit warnings that enabling them shifts diagnostics and may require recalibration. The second is making the package composable — extensions now work regardless of load order, and parameter assignment propagates to the derived rate arrays instead of being silently discarded. That second thread reads as the more consequential one: the 3.2.0 notes describe scalar edits that previously vanished and now accumulate, which is the kind of fix that changes what published model configurations actually computed.
◆ Prediction
Expect the experimental second-order scheme to move toward default-on once recalibration guidance exists, and the patch line to keep absorbing the documentation and website gaps that 3.2.1 started on.
Alternatives to ggstatsplot and mizer
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 ggstatsplot or mizer.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all ggstatsplot alternatives → · See all mizer alternatives →
Recent activity from ggstatsplot and mizer
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 15d agomizerpkgdown index fix for a man page added after the 3.2.0 build
- 25d agomizerParameter assignment rebuilds derived rates; extensions compose in any load order
- 1mo agomizerOpt-in second-order accurate scheme in the size variable
- 2mo agomizerDiffusion enters the McKendrick-von Foerster equation, ending a two-year gap ⚡
- 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
- 4mo agoggstatsplotInternal maintenance only
- 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
- 8mo agoggstatsplotContributor list updated in DESCRIPTION
- 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
- 11mo agoggstatsplotAdapted to the latest ggplot2 release
- 2y agomizerExternal encounter rate, and a split between given and calculated parameters
- 3y agomizerw_inf renamed to w_max to separate maximum size from von Bertalanffy asymptotic size
Frequently asked questions
What is the difference between ggstatsplot and mizer?
Both compete on the same themes — r-package — within Analytics. mizer is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 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 ggstatsplot better than mizer?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mizer is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 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 ggstatsplot?
Top ggstatsplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggstatsplot alternatives" section above for the current picks, or visit /alternatives/ggstatsplot for the full list with editorial commentary on each.
What are the best alternatives to mizer?
Top mizer alternatives in Analytics are ranked by recent ship velocity. Browse the "mizer alternatives" section above for the current picks, or visit /alternatives/mizer-r for the full list with editorial commentary on each.