compositional.mle
An MLE package rebuilt around composable solvers, then renamed to match.
A side-by-side editorial comparison of revdbayes and tulpa — release velocity, themes, recent moves, and the top alternatives to consider.
Extreme value sampling in pure upkeep mode, mostly answering to Rcpp and CRAN.
revdbayes performs Bayesian extreme value analysis using ratio-of-uniforms sampling, giving random samples rather than MCMC chains. Every entry in the visible window is filed under bug fixes and minor improvements. The most recent, 1.5.7, strips missing values before fitting the generalised Pareto MLE; the two before it are an Rcpp compatibility patch and a response to CRAN check failures that turned out to be false positives.
A Bayesian spatial engine reshaping itself so downstream packages own their own diagnostics.
tulpa is the C++/R inference engine sitting under a family of ecological occupancy packages, tagging releases several times a week in the 0.0.x range. The current window splits cleanly in two: an API move that turns its calibration and goodness-of-fit entry points into S3 generics, and a run of numerical-correctness work in the nested-Laplace grid. A notable share of releases exist to record a measurement that produced no code change at all.
revdbayes performs Bayesian extreme value analysis using ratio-of-uniforms sampling, giving random samples rather than MCMC chains. Every entry in the visible window is filed under bug fixes and minor improvements. The most recent, 1.5.7, strips missing values before fitting the generalised Pareto MLE; the two before it are an Rcpp compatibility patch and a response to CRAN check failures that turned out to be false positives.
The methods are settled and the release traffic is external: Rcpp issues, CRAN platform checks, documentation anchor requirements. Two of the six releases exist only because CRAN's check farm flagged something, and one of those flags resolved itself. Sibling package profileCI from the same maintainer has been more active, which suggests attention has moved to newer work rather than away from R entirely.
Expect further small releases driven by Rcpp or CRAN check changes rather than by the sampling methods.
tulpa is the C++/R inference engine sitting under a family of ecological occupancy packages, tagging releases several times a week in the 0.0.x range. The current window splits cleanly in two: an API move that turns its calibration and goodness-of-fit entry points into S3 generics, and a run of numerical-correctness work in the nested-Laplace grid. A notable share of releases exist to record a measurement that produced no code change at all.
The generics conversion and the new cross-Hessian return value point the same way: the engine is being reshaped into something downstream packages extend rather than wrap, with the extension points made explicit. The correctness fixes cluster tightly on the joint nested-Laplace driver — indefinite Hessians hitting negative pivots, chunk counts read from live machine load, grid cells silently dropped from a fit — which is where the remaining risk visibly sits. Reported numbers have moved more than once in this window, so the project is still finding cases where earlier answers were wrong rather than merely imprecise.
Expect the rest of the diagnostics layer to finish migrating onto generics, and continued hardening of the batched joint driver's dense path, which is the one route that recently diverged from its own single-species equivalent.
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 revdbayes or tulpa.
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.
A package retired in 2017 just got rewritten against R's public C API.
See all revdbayes alternatives → · See all tulpa alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. tulpa 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. tulpa 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 revdbayes alternatives in Analytics are ranked by recent ship velocity. Browse the "revdbayes alternatives" section above for the current picks, or visit /alternatives/revdbayes for the full list with editorial commentary on each.
Top tulpa alternatives in Analytics are ranked by recent ship velocity. Browse the "tulpa alternatives" section above for the current picks, or visit /alternatives/tulpa for the full list with editorial commentary on each.