metatools
SDTM supplemental-qualifier merging got sturdier, then the package went quiet for two years.
Comparison · Analytics
mlr3cmprsk vs nanonext
A side-by-side editorial comparison of mlr3cmprsk and nanonext — release velocity, themes, recent moves, and the top alternatives to consider.
mlr3cmprsk vs nanonext: at a glance
What is mlr3cmprsk?
Competing risks arrive in mlr3, going from a non-parametric baseline to Fine-Gray regression in seven weeks.
mlr3cmprsk extends mlr3 to competing-risks analysis: learners predicting cumulative incidence functions, plus measures to score them. It appeared in February 2026 and reached 0.0.5 by April, adding a Fine-Gray learner and a Brier score along the way. The version numbers say pre-release; the cadence says active build-out.
What is nanonext?
nanonext keeps shrinking its build requirements while adding messaging primitives.
The R binding to NNG ships roughly monthly. Since February the package added an HTTP server that can run synchronously or through the later event loop, a zero-copy device forwarder for building brokers and proxies, and support for pthread-enabled WebAssembly targets. Send operations now move the buffer straight into the NNG message, halving peak memory on serialized sends.
mlr3cmprsk vs nanonext: editorial side-by-side
mlr3cmprsk
0.0ANALYTICS
Competing risks arrive in mlr3, going from a non-parametric baseline to Fine-Gray regression in seven weeks.
◆ Current state
mlr3cmprsk extends mlr3 to competing-risks analysis: learners predicting cumulative incidence functions, plus measures to score them. It appeared in February 2026 and reached 0.0.5 by April, adding a Fine-Gray learner and a Brier score along the way. The version numbers say pre-release; the cadence says active build-out.
◆ Where it's heading
The package assembled a working evaluation stack fast. It started with the Aalen-Johansen estimator as a non-parametric baseline, added Fine-Gray as a regression alternative, then filled in the scoring side with an AUC refactor and a fixed-time Brier score. Development has run in lockstep with survdistr and mlr3extralearners, which picked up the dependency at 1.5.2.
◆ Prediction
The visible gaps are more learners — cause-specific Cox and boosting variants — and the tuning and pipeline integration the rest of mlr3 expects; the measure side currently looks further along than the model side.
nanonext
2.5ANALYTICS
nanonext keeps shrinking its build requirements while adding messaging primitives.
◆ Current state
The R binding to NNG ships roughly monthly. Since February the package added an HTTP server that can run synchronously or through the later event loop, a zero-copy device forwarder for building brokers and proxies, and support for pthread-enabled WebAssembly targets. Send operations now move the buffer straight into the NNG message, halving peak memory on serialized sends.
◆ Where it's heading
Two directions run in parallel. One is making the package installable anywhere — the build-time cmake dependency is gone, so compiling bundled NNG and Mbed TLS needs only a C compiler, and WebAssembly targets are supported. The other is raising the ceiling on what can be built on top: device_aio() for message forwarding, an HTTP and WebSocket server with a content map, and stream buffer control. Bug fixes in recent releases concentrate on memory safety in the bundled C sources.
◆ Prediction
Given the pace and the tight coupling declared in each release, expect the next version to track a mirai requirement and continue hardening the HTTP server paths that the last two releases have been leaking memory in.
Alternatives to mlr3cmprsk and nanonext
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 mlr3cmprsk or nanonext.
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logrx
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lobstr
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GSODR
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giscoR
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See all mlr3cmprsk alternatives → · See all nanonext alternatives →
Recent activity from mlr3cmprsk and nanonext
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 9d agonanonextMemory leaks and a TLS use-after-free fixed in the HTTP server
- 1mo agonanonextEvent-loop integration for HTTP and WebSocket callbacks
- 1mo agonanonextZero-copy message forwarding, and cmake dropped from the build ⚡
- 2mo agonanonextBuilds against pthread-enabled WebAssembly targets
- 3mo agonanonextSerialized sends drop a copy and halve peak memory
- 4mo agomlr3cmprskBrier score for competing risks and an AUC refactor
- 4mo agomlr3cmprskFine-Gray learner brings regression modelling to competing risks ⚡
- 4mo agonanonextBlocking HTTP server mode and stream buffer sizing
- 4mo agomlr3cmprskAalen-Johansen learner gains standard mlr3 properties
- 4mo agomlr3cmprskCIF interpolation pulled from survdistr
- 5mo agomlr3cmprskFirst release on mlr-org.r-universe
Frequently asked questions
What is the difference between mlr3cmprsk and nanonext?
They serve adjacent needs but don't currently overlap on shipped themes. nanonext 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 mlr3cmprsk better than nanonext?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nanonext 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.
What are the best alternatives to mlr3cmprsk?
Top mlr3cmprsk alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3cmprsk alternatives" section above for the current picks, or visit /alternatives/mlr3cmprsk for the full list with editorial commentary on each.
What are the best alternatives to nanonext?
Top nanonext alternatives in Analytics are ranked by recent ship velocity. Browse the "nanonext alternatives" section above for the current picks, or visit /alternatives/nanonext for the full list with editorial commentary on each.