Okta
Okta's developer blog is a Cross App Access campaign, now diluted by advocacy-team storytelling.
A side-by-side editorial comparison of forestploter and logbin — release velocity, themes, recent moves, and the top alternatives to consider.
A forest plot package that keeps handing users control of one more graphical detail.
forestploter draws forest plots where the layout is driven by the data frame itself, so text columns and confidence intervals sit in the same grid. The theme function has become the package's centre of gravity: it now controls graphical parameters for titles, legends, axis, arrow labels, footnotes, and reference lines, with multi-column and row-order legend controls added most recently. Two releases shipped nine minutes apart in April 2026 after a two-year gap, deprecating some theme parameters, removing inter-cell gaps, and improving tick breaks.
Relative-risk regression that converges where glm fails, under an unreadable tag order
logbin fits log-binomial models to estimate relative risk, a fit standard glm frequently fails to converge on because of the constrained parameter space. Its answer is a choice of algorithms — adaptive barrier, combinatorial EM, and expectation-maximisation on an overparameterised model — selected through a method argument and optionally accelerated with turboEM. The most recent release, in April 2025, replaces the variance-covariance calculation in summary.logbin so it matches summary.glm, and adds a testthat suite.
forestploter draws forest plots where the layout is driven by the data frame itself, so text columns and confidence intervals sit in the same grid. The theme function has become the package's centre of gravity: it now controls graphical parameters for titles, legends, axis, arrow labels, footnotes, and reference lines, with multi-column and row-order legend controls added most recently. Two releases shipped nine minutes apart in April 2026 after a two-year gap, deprecating some theme parameters, removing inter-cell gaps, and improving tick breaks.
The direction has been consistent for four years: whatever a user might want to restyle eventually becomes an argument. Point size stopped being transformed, cell height adjustment was removed as unwanted, legends gained size, column, and fill-order control, and vertical lines learned to extend the full plot height and to draw beneath the whiskers. The one structural move was 1.1.0, which let callers supply their own confidence-interval and summary drawing functions — turning a fixed renderer into an extensible one. Everything since has been the arguments that extensibility did not cover.
The latest release deprecates theme parameters rather than adding them, which suggests the next one consolidates the theme surface that has grown for four years rather than extending it further.
logbin fits log-binomial models to estimate relative risk, a fit standard glm frequently fails to converge on because of the constrained parameter space. Its answer is a choice of algorithms — adaptive barrier, combinatorial EM, and expectation-maximisation on an overparameterised model — selected through a method argument and optionally accelerated with turboEM. The most recent release, in April 2025, replaces the variance-covariance calculation in summary.logbin so it matches summary.glm, and adds a testthat suite.
The method work concluded in 2021 and the package has since been aligned with base R conventions rather than extended: the vcov calculation now mirrors glm's, and earlier releases added the contrasts, qr, R and effects components so standard glm S3 methods such as influence() and plot() work on logbin objects. Be warned that the feed's tag order is unusable — versions 2.0, 2.0.1, 2.0.2 and 2.0.4 were all pushed within ninety seconds on 23 July 2021 in non-monotonic order, while 2.0.3 carries a 2017 timestamp and restates 2.0.2's notes. Read the bodies, not the sequence.
Expect continued alignment with glm conventions and occasional CRAN maintenance; the algorithm set has been stable for four years and nothing in these entries suggests another is planned.
Other Infra & APIs 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 forestploter or logbin.
Okta's developer blog is a Cross App Access campaign, now diluted by advocacy-team storytelling.
A leaf-temperature model that finished its job in 2020 and has stayed finished
A credential platform assembled two or three pull requests at a time, never a headline
Search without knowing the field — SigNoz keeps lowering the cost of not knowing your schema
A NOAA Fisheries colour palette that ships when the branding guide changes
A genetic-mapping mainstay that now points new users toward MAPpoly at load time
See all forestploter alternatives → · See all logbin alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. forestploter and logbin 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. forestploter and logbin 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 Infra & APIs products to evaluate alongside.
Top forestploter alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "forestploter alternatives" section above for the current picks, or visit /alternatives/forestploter for the full list with editorial commentary on each.
Top logbin alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "logbin alternatives" section above for the current picks, or visit /alternatives/logbin for the full list with editorial commentary on each.