nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Comparison · Analytics
bayestools vs hydroloom
A side-by-side editorial comparison of bayestools and hydroloom — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
bayestools vs hydroloom: at a glance
What is bayestools?
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
BayesTools provides the shared JAGS fitting, prior and summary infrastructure that the author's meta-analysis packages build on. The 0.2.x line filled in modeling primitives — prior_mixture() and mixed-posterior objects in 0.2.18, expression-valued priors and lme4-style uncorrelated random effects in 0.2.20, then a run of small diagnostic fixes for mixture and spike-and-slab priors. Version 0.3.0 in May 2026 adds automatic standardization of continuous predictors, default priors for unspecified factor and continuous terms, and functions to transform prior and posterior samples back to the original scale.
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.
bayestools vs hydroloom: editorial side-by-side
bayestools
0.0ANALYTICS
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
◆ Current state
BayesTools provides the shared JAGS fitting, prior and summary infrastructure that the author's meta-analysis packages build on. The 0.2.x line filled in modeling primitives — prior_mixture() and mixed-posterior objects in 0.2.18, expression-valued priors and lme4-style uncorrelated random effects in 0.2.20, then a run of small diagnostic fixes for mixture and spike-and-slab priors. Version 0.3.0 in May 2026 adds automatic standardization of continuous predictors, default priors for unspecified factor and continuous terms, and functions to transform prior and posterior samples back to the original scale.
◆ Where it's heading
This package's releases are best read against what depends on them. The 0.2.x fixes track features appearing in RoBMA one version later, and 0.3.0 landed a single day before RoBMA 4.0.0 — the standardization and sample-transformation functions are the substrate that rewrite needed. The direction of the work is toward sensible defaults: default priors by predictor type, automatic standardization for sampling stability, and transformation back to interpretable scale so the convenience does not cost the user their units.
◆ Prediction
Given how tightly its releases track downstream needs, the next version is most likely driven by gaps surfacing in RoBMA 4.0.x rather than by independent feature work.
hydroloom
0.0ANALYTICS
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 bayestools 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 bayestools or hydroloom.
susier
Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs
UCell
A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next
detectseparation
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
brglm2
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
robma
RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy
See all bayestools alternatives → · See all hydroloom alternatives →
Recent activity from bayestools and hydroloom
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agohydroloomhydroloom v1.2.0 ⚡
- 3mo agobayestoolsAdds automatic predictor standardization and type-based default priors
- 5mo agohydroloomTest tolerances relaxed for CRAN Fedora checks
- 5mo agohydroloomNetwork subsetting and divergence-routed accumulation
- 8mo agobayestoolsBayesTools 0.2.23
- 8mo agobayestoolsBayesTools 0.2.22
- 10mo agohydroloomSort and indexing fixes
- 11mo agobayestoolsBayesTools 0.2.21
- 1y agobayestoolsBayesTools 0.2.20
- 1y agobayestoolsBayesTools 0.2.19
- 1y agohydroloomUpmain and downmain navigation for non-dendritic networks
- 2y agohydroloomInitial release completing the nhdplusTools migration
Frequently asked questions
What is the difference between bayestools and hydroloom?
Both compete on the same themes — r-package — within Analytics. bayestools and hydroloom 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 bayestools better than hydroloom?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bayestools and hydroloom 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 Analytics products to evaluate alongside.
What are the best alternatives to bayestools?
Top bayestools alternatives in Analytics are ranked by recent ship velocity. Browse the "bayestools alternatives" section above for the current picks, or visit /alternatives/bayestools 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.