exametrika
A test-theory package that grew into a graphical-model toolkit, now spending its releases paying down the API debt that growth created.
Comparison · Infra & APIs
nuggets vs profileCI
A side-by-side editorial comparison of nuggets and profileCI — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
nuggets vs profileCI: at a glance
What is nuggets?
nuggets keeps compounding on the 2.0 rewrite — more pattern families, lighter install.
nuggets searches for association rules, contrasts and other conditional patterns in the GUHA tradition, with a C++ core behind dig() and an interactive explore() app for reading results. Since the 2.0 rewrite of that core, every release has widened the same three surfaces: more pattern families to mine, more of explore() to inspect them in, and steady performance work underneath. The most recent tag optimises dig() on sparse crisp data with a sparse bit chain and adds clustering characteristics to explore() for association rules.
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.
nuggets vs profileCI: editorial side-by-side
nuggets
2.5INFRA · APIS
nuggets keeps compounding on the 2.0 rewrite — more pattern families, lighter install.
◆ Current state
nuggets searches for association rules, contrasts and other conditional patterns in the GUHA tradition, with a C++ core behind dig() and an interactive explore() app for reading results. Since the 2.0 rewrite of that core, every release has widened the same three surfaces: more pattern families to mine, more of explore() to inspect them in, and steady performance work underneath. The most recent tag optimises dig() on sparse crisp data with a sparse bit chain and adds clustering characteristics to explore() for association rules.
◆ Where it's heading
Two forces are shaping the package. One is coverage: baseline, complement and paired-baseline contrasts, correlations, tautologies, ancestors and clustering have all been added as first-class dig_ or explore_ surfaces, so the same search engine now answers a widening set of questions. The other is weight — Shiny packages moved from Imports to Suggests, BH and RcppThread dropped, XSIMD updated, parse_condition() rewritten in C++ — which keeps a package with an interactive app from forcing that app's dependencies on every user. Deprecations are handled through lifecycle rather than removed abruptly.
◆ Prediction
Expect the sparse-data optimisation to extend from crisp to fuzzy data, and explore() to keep gaining tabs as each new pattern family lands, on the roughly six-week cadence the 2.2 line has held.
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.
Alternatives to nuggets and profileCI
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 nuggets or profileCI.
projoint
projoint spent a year on CRAN paperwork, then shipped a correctness fix it flagged itself.
eratosthenes
eratosthenes spends 0.1.0 hardening inputs rather than adding chronology methods.
dqcheckr
dqcheckr adds drift analysis, then removes the YAML a user had to hand-write.
lifecontingencies
An actuarial mainstay spends its releases on CI plumbing, not on new mathematics.
EDAForge
EDAForge is a data-quality auditor renamed mid-flight, still finding its CRAN footing.
See all nuggets alternatives → · See all profileCI alternatives →
Recent activity from nuggets and profileCI
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 27d agonuggetsSparse bit chain speeds dig(); explore() gains clustering
- 2mo agonuggetspartition() gains .subsets; geom_diamond() layout improved
- 5mo agonuggetsexplore() covers contrasts and correlations; dig_ancestors() added
- 6mo agonuggetsCritical explore() bug fixed; is_logicalish() added
- 6mo agonuggetsShiny deps moved to Suggests; BH and RcppThread dropped
- 6mo agoprofileCICubic spline interpolation replaces a quadratic that could fail
- 7mo agoprofileCICRAN 1.0.0 release of profile-likelihood interval computation
- 8mo agonuggetscluster_associations() and add_interest() arrive; C++ condition parser
- 1y agoprofileCIInfinite limits and bounded profiling ranges handled
Frequently asked questions
What is the difference between nuggets and profileCI?
Both compete on the same themes — r-package — within Infra & APIs. nuggets 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.
Is nuggets better than profileCI?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nuggets 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 Infra & APIs products to evaluate alongside.
What are the best alternatives to nuggets?
Top nuggets alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "nuggets alternatives" section above for the current picks, or visit /alternatives/nuggets for the full list with editorial commentary on each.
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.