HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
Comparison · Infra & APIs
adjustedCurves vs fdacluster
A side-by-side editorial comparison of adjustedCurves and fdacluster — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
adjustedCurves vs fdacluster: at a glance
What is adjustedCurves?
A survival curve package spending release after release correcting its own estimates
adjustedCurves computes confounder-adjusted survival and cumulative incidence curves across a range of estimators - IPTW, AIPTW, Aalen-Johansen, direct standardisation - with support for multiple imputation and bootstrapping. The recent releases are dominated by corrections to numbers the package already reported. Version 0.11.4 fixed cumulative incidence estimates under method="aalen_johansen" that were being read one time step early, which the maintainer notes could differ substantially when events are few, and added risk and event counts to the ggsurvplot conversion including correctly pooled values under multiple imputation.
What is fdacluster?
Functional data clustering grew from one algorithm into a comparable suite
fdacluster clusters functional data while separating amplitude from phase variation, aligning curves as part of the clustering rather than before it. The algorithm set covers k-means, hierarchical clustering and DBSCAN, all producing a common caps result object so runs can be compared directly. Version 0.4.0 tightened the interface with is_domain_interval and transformation arguments describing the input data, added compatibility checking between incompatible option combinations, and split the L2 and normalized L2 distances into separate C++ classes to enforce that plain L2 cannot be combined with dilation or affine warping it is not invariant to.
adjustedCurves vs fdacluster: editorial side-by-side
adjustedCurves
0.0INFRA · APIS
A survival curve package spending release after release correcting its own estimates
◆ Current state
adjustedCurves computes confounder-adjusted survival and cumulative incidence curves across a range of estimators - IPTW, AIPTW, Aalen-Johansen, direct standardisation - with support for multiple imputation and bootstrapping. The recent releases are dominated by corrections to numbers the package already reported. Version 0.11.4 fixed cumulative incidence estimates under method="aalen_johansen" that were being read one time step early, which the maintainer notes could differ substantially when events are few, and added risk and event counts to the ggsurvplot conversion including correctly pooled values under multiple imputation.
◆ Where it's heading
Multiple imputation is the recurring fault line. The standard error pooling formula was implemented incorrectly until 0.11.2, then fixed again in 0.11.3 for the bootstrapping-plus-imputation combination, and 0.11.4 added the pooled risk table values that had previously been omitted entirely. A separate thread quietly removed capability: tmle and ostmle methods went in 0.10.0, and tmle support was pulled again in 0.11.1 after the concrete package left CRAN. Feature work does happen - risk tables, contrast arguments, the extend_to_last control on IPTW curves - but it is outweighed by correction.
◆ Prediction
Expect continued estimator-level corrections rather than new methods, and a possible return of tmle support if its upstream dependency returns to CRAN, since the removal was described as temporary.
fdacluster
0.0INFRA · APIS
Functional data clustering grew from one algorithm into a comparable suite
◆ Current state
fdacluster clusters functional data while separating amplitude from phase variation, aligning curves as part of the clustering rather than before it. The algorithm set covers k-means, hierarchical clustering and DBSCAN, all producing a common caps result object so runs can be compared directly. Version 0.4.0 tightened the interface with is_domain_interval and transformation arguments describing the input data, added compatibility checking between incompatible option combinations, and split the L2 and normalized L2 distances into separate C++ classes to enforce that plain L2 cannot be combined with dilation or affine warping it is not invariant to.
◆ Where it's heading
The trajectory runs from method implementation toward guardrails and portability. Early releases added capability; recent ones prevent misuse and reduce weight - dplyr, forcats, tidyr and purrr removed in 0.4.0, furrr swapped for future.apply - while 0.4.2 is entirely C++ correctness, replacing Armadillo's whole-object finiteness check with scalar std::isfinite and fixing an integer overflow in linear index computation that broke large datasets. Cadence is roughly one release a year.
◆ Prediction
Given that the last two releases were dependency reduction and numerical correctness rather than method work, expect the next to continue in that vein unless a new clustering algorithm is contributed.
Alternatives to adjustedCurves and fdacluster
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 adjustedCurves or fdacluster.
bsvarSIGNs
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
estimatr
Fast design-based estimators for experiments, coasting on CRAN patches.
ggdist
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
ipaddress
IP address vectors for R that hit 1.0 and then went quiet.
ltertools
A column-key toolkit for stitching decades of ecological field data into one table.
See all adjustedCurves alternatives → · See all fdacluster alternatives →
Recent activity from adjustedCurves and fdacluster
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agoadjustedCurvesOff-by-one-step error corrected in cumulative incidence estimates
- 7mo agofdaclusterInteger overflow fixed for large datasets, C++ finiteness checks corrected
- 1y agoadjustedCurvesIPTW curves can now extend to the last observed time
- 1y agofdaclusterParallel worker setup and an acronym correction
- 1y agofdaclusterInput description arguments and enforced distance-warping compatibility
- 2y agoadjustedCurvesDropped arguments and a wrong multiple-imputation pooling formula
- 2y agoadjustedCurvesRisk tables, contrast consolidation and faster bootstrapping
- 3y agofdaclusterMedian centroids and centroids defined on unioned grids
- 3y agofdaclusterNamespace notation and optional dependency guards
- 3y agofdaclusterHierarchical clustering, DBSCAN and a shared result class arrive together ⚡
- 3y agoadjustedCurvestmle and ostmle methods dropped
- 3y agoadjustedCurvesDependency compatibility and installation documentation
Frequently asked questions
What is the difference between adjustedCurves and fdacluster?
Both compete on the same themes — r-package — within Infra & APIs. adjustedCurves and fdacluster 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 adjustedCurves better than fdacluster?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. adjustedCurves and fdacluster 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 adjustedCurves?
Top adjustedCurves alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "adjustedCurves alternatives" section above for the current picks, or visit /alternatives/adjustedcurves for the full list with editorial commentary on each.
What are the best alternatives to fdacluster?
Top fdacluster alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "fdacluster alternatives" section above for the current picks, or visit /alternatives/fdacluster for the full list with editorial commentary on each.