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compositional.mle vs procs

A side-by-side editorial comparison of compositional.mle and procs — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

compositional.mle vs procs: at a glance

Featurecompositional.mleprocs
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmaximum-likelihood, optimization, functional-api, cranstatistics, sas-migration, r-package, clinical-reporting
Last editorial update23m ago1h ago
WebsiteVisit →Visit →

What is compositional.mle?

An MLE package rebuilt around composable solvers, then renamed to match.

compositional.mle performs numerical maximum likelihood estimation in R, with the optimisation strategy expressed as composed pieces rather than configured up front. It began in November 2025 as numerical.mle, a configuration-object package with fixed solvers. The v0.2.0 rewrite replaced that with solver factories sharing a uniform signature and operators for chaining and racing them, and renamed the package accordingly. The two most recent releases are CRAN submission work.

Read the full compositional.mle trajectory →

What is procs?

An R package rebuilding SAS procedures one PROC at a time, now filling in their options.

procs reimplements SAS statistical procedures — FREQ, MEANS, TTEST, REG, SORT, TRANSPOSE — as R functions returning both datasets and report-ready output, as part of the r-sassy suite. The catalogue of procedures is largely assembled; recent releases concentrate on the parameters each one accepts rather than on adding new procedures. Validation documentation is maintained alongside the code, consistent with the regulated environments the suite targets.

Read the full procs trajectory →

compositional.mle vs procs: editorial side-by-side

C0.0

An MLE package rebuilt around composable solvers, then renamed to match.

◆ Current state

compositional.mle performs numerical maximum likelihood estimation in R, with the optimisation strategy expressed as composed pieces rather than configured up front. It began in November 2025 as numerical.mle, a configuration-object package with fixed solvers. The v0.2.0 rewrite replaced that with solver factories sharing a uniform signature and operators for chaining and racing them, and renamed the package accordingly. The two most recent releases are CRAN submission work.

◆ Where it's heading

The arc is a design idea overtaking an implementation: version 0.1.0 exposed configuration functions and named solvers, version 0.2.0 turned solvers into values that can be sequenced with %>>%, raced with %|%, restarted, or conditionally refined, and separated the statistical problem from the optimisation strategy. Since then all effort has gone into CRAN acceptance, dead code removal, policy compliance, validation fixes. That is a package that redesigned itself early and is now trying to get through the door.

◆ Prediction

With the composable API settled, the next work will most likely be additional solvers and transformers plugged into the existing operators rather than another redesign.

P
procs
ANALYTICS
0.0

An R package rebuilding SAS procedures one PROC at a time, now filling in their options.

◆ Current state

procs reimplements SAS statistical procedures — FREQ, MEANS, TTEST, REG, SORT, TRANSPOSE — as R functions returning both datasets and report-ready output, as part of the r-sassy suite. The catalogue of procedures is largely assembled; recent releases concentrate on the parameters each one accepts rather than on adding new procedures. Validation documentation is maintained alongside the code, consistent with the regulated environments the suite targets.

◆ Where it's heading

The work has shifted from breadth to fidelity: where earlier releases introduced whole procedures, recent ones add the options a SAS user expects to find on them, most visibly the where parameter spread across five functions at once and plotting support across three. Statistical output is being widened too, with AIC and adjusted Chi-Square appearing. The remaining gap is per-procedure option coverage rather than missing procedures.

◆ Prediction

Expect continued option-level parity work on the existing procedures, with new statistics added to their output tables, rather than a new proc_* function.

Alternatives to compositional.mle and procs

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 compositional.mle or procs.

See all compositional.mle alternatives → · See all procs alternatives →

Recent activity from compositional.mle and procs

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 2mo agoprocsproc_ttest() gains sides, freq and weight parameters
  2. 4mo agoprocsA where parameter arrives across five procedures
  3. 6mo agocompositional.mleParallel racing fixed under the future package
  4. 6mo agocompositional.mleDead code removed and CRAN policy compliance work
  5. 8mo agocompositional.mleSolvers become composable values, and the package is renamed
  6. 8mo agocompositional.mleFirst release as numerical.mle, built on configuration objects
  7. 8mo agoprocsAdjusted Chi-Square added, altering the proc_freq() table
  8. 2y agoprocsproc_reg() added for regression
  9. 2y agoprocsOrdered-factor handling fixed across three procedures
  10. 2y agoprocsproc_ttest() added, plus factor casting on proc_sort()

Frequently asked questions

What is the difference between compositional.mle and procs?

Both compete on the same themes — r-package — within Analytics. compositional.mle and procs 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.

Is compositional.mle better than procs?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. compositional.mle and procs 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 Analytics products to evaluate alongside.

What are the best alternatives to compositional.mle?

Top compositional.mle alternatives in Analytics are ranked by recent ship velocity. Browse the "compositional.mle alternatives" section above for the current picks, or visit /alternatives/compositional-mle for the full list with editorial commentary on each.

What are the best alternatives to procs?

Top procs alternatives in Analytics are ranked by recent ship velocity. Browse the "procs alternatives" section above for the current picks, or visit /alternatives/procs for the full list with editorial commentary on each.