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Comparison · Infra & APIs
profileCI vs SLmetrics
A side-by-side editorial comparison of profileCI and SLmetrics — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
profileCI vs SLmetrics: at a glance
What is profileCI?
Profile-likelihood confidence intervals for any fitted model, in a feed that publishes out of order.
profileCI computes confidence intervals from the profile log-likelihood for user-supplied fitted models, generalising what confint.glm does for GLMs to any model object exposing a log-likelihood. The releases handle the awkward cases that make profiling fail in practice: infinite limits when the profile never drops below the interval threshold, bounded profiling ranges, and interpolation that breaks down near the limits. Only convex log-likelihoods are supported, so disjoint intervals are out of scope by design.
What is SLmetrics?
A young ML metrics package rewrote its own backend twice in six months chasing speed.
SLmetrics provides supervised learning evaluation metrics for R — confusion matrices, classification and regression measures, ROC and precision-recall curves — with the computation pushed into C++. After a series of pre-releases it now runs on an Armadillo backend, supports OpenMP parallelism and LAPACK/BLAS, and reports 5-20x speedups over its earlier implementations. The API has been reshaped for extensibility, with an estimator argument replacing the fixed aggregation options.
profileCI vs SLmetrics: editorial side-by-side
profileCI
0.0INFRA · APIS
Profile-likelihood confidence intervals for any fitted model, in a feed that publishes out of order.
◆ Current state
profileCI computes confidence intervals from the profile log-likelihood for user-supplied fitted models, generalising what confint.glm does for GLMs to any model object exposing a log-likelihood. The releases handle the awkward cases that make profiling fail in practice: infinite limits when the profile never drops below the interval threshold, bounded profiling ranges, and interpolation that breaks down near the limits. Only convex log-likelihoods are supported, so disjoint intervals are out of scope by design.
◆ Where it's heading
Work is concentrated on numerical reliability rather than scope: 1.1.1 replaced quadratic with monotonic cubic spline interpolation because the quadratic form could fail, and corrected parameter values stored near the confidence limits. The feed publishes these out of order, with the v1.0.0 entry stamped six months after v1.1.0 and carrying the package's full description rather than a changelog, so release order should be read from the version numbers rather than the dates. The same maintainer's revdbayes has been in pure maintenance across this period, which places profileCI as the more active project.
◆ Prediction
Expect further robustness work at the profiling limits and more logLikFn methods for common model classes, following the nls method added in 1.1.0.
SLmetrics
0.0INFRA · APIS
A young ML metrics package rewrote its own backend twice in six months chasing speed.
◆ Current state
SLmetrics provides supervised learning evaluation metrics for R — confusion matrices, classification and regression measures, ROC and precision-recall curves — with the computation pushed into C++. After a series of pre-releases it now runs on an Armadillo backend, supports OpenMP parallelism and LAPACK/BLAS, and reports 5-20x speedups over its earlier implementations. The API has been reshaped for extensibility, with an estimator argument replacing the fixed aggregation options.
◆ Where it's heading
Every release in this timeline is about making the same metrics compute faster or compose better. The backend moved from Rcpp to plain C++, gained OpenMP, then was ported wholesale from Eigen to Armadillo with heavy templating. In parallel the author has been widening the API's joints: generic S3 signatures, an extensible estimator argument, and function signatures loose enough that wrapping packages can rename arguments. Bundled datasets and embedded formulas in the docs point at teaching and benchmarking use. The package still labels itself pre-release, which is consistent with how freely it has broken argument names along the way.
◆ Prediction
A stable non-pre-release version is the natural next step now that the backend has settled on Armadillo, though the repeated willingness to rename arguments suggests more API churn may come first.
Alternatives to profileCI and SLmetrics
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 profileCI or SLmetrics.
rJavaEnv
The R package that installs Java for you stopped needing an update every time Java ships.
traits.build
The AusTraits engine, generalised for anyone's trait database, now links measurements to real specimens.
rwasm
The toolchain that gets R packages into the browser is optimising for payload size, not features.
Fail2Ban
Fail2Ban finally ships 1.1.1 after 14 months in beta, with a botched deb package on the way out the door
plogr
A logging header for Rcpp packages that sat untouched for nine years, then changed how it switches on
See all profileCI alternatives → · See all SLmetrics alternatives →
Recent activity from profileCI and SLmetrics
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agoprofileCICubic spline interpolation replaces a quadratic that could fail
- 7mo agoprofileCICRAN 1.0.0 release of profile-likelihood interval computation
- 1y agoprofileCIInfinite limits and bounded profiling ranges handled
- 1y agoSLmetricsArmadillo backend brings 5-20x speedups and an extensible metrics API ⚡
- 1y agoSLmetricsConsistent S3 signatures and three bundled datasets
- 1y agoSLmetricsRegression metrics 2-10x faster with reworked OpenMP controls
- 1y agoSLmetricsOpenMP parallelism and a soft-label entropy family
- 1y agoSLmetricsCross-entropy loss and relative RMSE with three normalisations
- 1y agoSLmetricsSample weights flow through the confusion matrix
Frequently asked questions
What is the difference between profileCI and SLmetrics?
Both compete on the same themes — r-package — within Infra & APIs. profileCI and SLmetrics 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 profileCI better than SLmetrics?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. profileCI and SLmetrics 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.
What are the best alternatives to profileCI?
Top profileCI alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "profileCI alternatives" section above for the current picks, or visit /alternatives/profileci for the full list with editorial commentary on each.
What are the best alternatives to SLmetrics?
Top SLmetrics alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "SLmetrics alternatives" section above for the current picks, or visit /alternatives/slmetrics for the full list with editorial commentary on each.