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cTMed vs hydroloom

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

Shared themes:r-package

cTMed vs hydroloom: at a glance

FeaturecTMedhydroloom
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesmediation-analysis, continuous-time-models, r-package, statistical-methodshydrology, network-analysis, geospatial, r-package
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is cTMed?

Continuous-time mediation effects get standardized centrality, six years into steady patch work

cTMed computes direct, indirect and total effects for continuous-time mediation models, with delta-method, Monte Carlo and bootstrap variants of each. Development is a long run of patch releases from the jeksterslab account, roughly every two months, each adding a function or two. The latest adds standardized centrality measures and allows a diagonal sigma across ten standardized estimators.

Read the full cTMed trajectory →

What is hydroloom?

USGS puts a type system over its river network toolkit so errors surface at dispatch

hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.

Read the full hydroloom trajectory →

cTMed vs hydroloom: editorial side-by-side

C
cTMed
ANALYTICS
2.5

Continuous-time mediation effects get standardized centrality, six years into steady patch work

◆ Current state

cTMed computes direct, indirect and total effects for continuous-time mediation models, with delta-method, Monte Carlo and bootstrap variants of each. Development is a long run of patch releases from the jeksterslab account, roughly every two months, each adding a function or two. The latest adds standardized centrality measures and allows a diagonal sigma across ten standardized estimators.

◆ Where it's heading

The package is filling out a matrix rather than changing shape: for each effect type there is a delta-method, a Monte Carlo and a bootstrap path, and each release closes another cell. The 2025 releases were largely externally forced — an Armadillo 15.0.x transition at CRAN, a citation addition after the Psychological Methods paper landed — which suggests the statistical core has been settled since the 1.0.6 standardization revision.

◆ Prediction

The diagonal-sigma option has now reached the standardized estimators; extending it to the remaining unstandardized variants is the obvious next cell to fill.

H
hydroloom
ANALYTICS
0.0

USGS puts a type system over its river network toolkit so errors surface at dispatch

◆ Current state

hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.

◆ Where it's heading

The package spent its first releases porting and broadening — non-dendritic network support, divergence routing, subsetting that follows diversions out of a basin — and has now turned to making that surface safe to use. The class hierarchy is the structural expression of that turn: instead of every function re-checking whether a data frame has the columns it needs, the type carries the guarantee. The explicit outlet rule resolves a category of failure where valid networks errored on NA or orphan toid values.

◆ Prediction

The release notes flag that subclass attributes are stripped by standard dplyr operations, which is the kind of rough edge that usually generates follow-up work — expect attribute preservation or restoration helpers next.

Alternatives to cTMed and hydroloom

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 cTMed or hydroloom.

See all cTMed alternatives → · See all hydroloom alternatives →

Recent activity from cTMed and hydroloom

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

  1. 26d agocTMedStandardized centrality measures and diagonal-sigma support
  2. 2mo agohydroloomhydroloom v1.2.0
  3. 5mo agohydroloomTest tolerances relaxed for CRAN Fedora checks
  4. 5mo agohydroloomNetwork subsetting and divergence-routed accumulation
  5. 6mo agocTMedMinor method edits
  6. 10mo agocTMedPackage citation added for the Psychological Methods paper
  7. 10mo agocTMedArmadillo 15.0.x compatibility for CRAN
  8. 10mo agohydroloomSort and indexing fixes
  9. 1y agocTMedStandardization reworked around the steady-state covariance matrix
  10. 1y agocTMedBootstrap centrality estimators and MCPhiSigma()
  11. 1y agohydroloomUpmain and downmain navigation for non-dendritic networks
  12. 2y agohydroloomInitial release completing the nhdplusTools migration

Frequently asked questions

What is the difference between cTMed and hydroloom?

Both compete on the same themes — r-package — within Analytics. cTMed 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 cTMed better than hydroloom?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cTMed 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 cTMed?

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

What are the best alternatives to hydroloom?

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