compositional.mle
An MLE package rebuilt around composable solvers, then renamed to match.
A side-by-side editorial comparison of ggguides and modelbpp — release velocity, themes, recent moves, and the top alternatives to consider.
Three releases in one day to make legend positioning finally do what the docs said.
ggguides is a helper layer over ggplot2's guide system, exposing legend placement and styling through small named functions instead of raw theme() calls. On 23 April 2026 it shipped 1.1.7, 1.1.8 and 1.1.9 within thirteen hours, each fixing a different path by which the justification argument silently did nothing. The common root cause is that ggplot2 3.5 split legend.justification into side-specific theme elements, and ggguides was still writing to the generic fallback.
A structural-equation model comparison package whose feed carries links, not release notes.
modelbpp computes model-implied Bayesian posterior probabilities for structural equation models, one of several R packages from the same author covering moderation, mediation and model-comparison workflows. Its release feed is not a changelog: every entry points at the package website rather than describing what changed, so the substance of each release is not visible here. Version numbering has moved steadily from 0.1.x to 0.4.0 across roughly three years.
ggguides is a helper layer over ggplot2's guide system, exposing legend placement and styling through small named functions instead of raw theme() calls. On 23 April 2026 it shipped 1.1.7, 1.1.8 and 1.1.9 within thirteen hours, each fixing a different path by which the justification argument silently did nothing. The common root cause is that ggplot2 3.5 split legend.justification into side-specific theme elements, and ggguides was still writing to the generic fallback.
The package is in the phase where a wrapper meets the reality of the API it wraps. All three same-day releases are the same bug found in successive entry points: legend_inside(), then the four side functions, then legend_style(by = ). Along the way the fix work produced a real feature, a justification argument on the side legend functions. The pattern of a single reporter driving three consecutive releases suggests the surface is being audited rather than randomly patched.
Expect a consolidation release that audits the remaining theme elements ggguides writes to against ggplot2 3.5 semantics, rather than another single-path fix.
modelbpp computes model-implied Bayesian posterior probabilities for structural equation models, one of several R packages from the same author covering moderation, mediation and model-comparison workflows. Its release feed is not a changelog: every entry points at the package website rather than describing what changed, so the substance of each release is not visible here. Version numbering has moved steadily from 0.1.x to 0.4.0 across roughly three years.
What can be read from this feed is cadence rather than content — releases clustered noticeably more tightly through 2026 than in the preceding two years, with three in five months against two in the prior eighteen. Because the entries carry no detail, any statement about what is being built would be speculation. The pattern of a stable CRAN package accelerating its release rate is the only reliable signal available.
The feed does not describe its changes, so the direction of development cannot be read from these entries; the accelerating 2026 cadence is the only thing it supports.
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 ggguides or modelbpp.
An MLE package rebuilt around composable solvers, then renamed to match.
nabla dropped its C++ engine to chase exact derivatives at any order.
Eight months from first release to keyring caching and workload identity.
A research-project workflow package where the interesting work is in the plumbing.
A cyclomatic complexity checker that ships once every couple of years, and lands when it does.
Extreme value sampling in pure upkeep mode, mostly answering to Rcpp and CRAN.
See all ggguides alternatives → · See all modelbpp alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. modelbpp is currently shipping more aggressively (velocity 2.5 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. modelbpp is currently shipping more aggressively (velocity 2.5 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.
Top ggguides alternatives in Analytics are ranked by recent ship velocity. Browse the "ggguides alternatives" section above for the current picks, or visit /alternatives/ggguides for the full list with editorial commentary on each.
Top modelbpp alternatives in Analytics are ranked by recent ship velocity. Browse the "modelbpp alternatives" section above for the current picks, or visit /alternatives/modelbpp for the full list with editorial commentary on each.