cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
Comparison · Analytics
SSN2 vs tulpaRatio
A side-by-side editorial comparison of SSN2 and tulpaRatio — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:spatial-statisticsr-package
SSN2 vs tulpaRatio: at a glance
What is SSN2?
Stream-network spatial models learning to run on data that no longer fits in memory
SSN2 fits spatial statistical models on stream networks, where covariance follows flow-connected distance along the network rather than straight-line distance. It is the maintained successor to the original SSN package, published through JOSS in 2024, and leans on spmodel for its underlying model machinery. Recent releases have concentrated on the constraint that binds this class of model hardest: the distance matrix.
What is tulpaRatio?
A Bayesian ratio-modelling package that threw out its Stan dependency and wrote its own sampler
ratiod models ratios, rates and proportions hierarchically, with the stated position that a ratio is a derived quantity and inference should run on the latent numerator and denominator processes rather than their quotient. The 1.0.0 release shipped a native HMC/NUTS backend, removing the Stan dependency that packages in this space normally take as given. Everything since has been sampler optimisation, benchmarked against the Stan implementations it replaced.
SSN2 vs tulpaRatio: editorial side-by-side
SSN2
0.0ANALYTICS
Stream-network spatial models learning to run on data that no longer fits in memory
◆ Current state
SSN2 fits spatial statistical models on stream networks, where covariance follows flow-connected distance along the network rather than straight-line distance. It is the maintained successor to the original SSN package, published through JOSS in 2024, and leans on spmodel for its underlying model machinery. Recent releases have concentrated on the constraint that binds this class of model hardest: the distance matrix.
◆ Where it's heading
The first year was about establishing credibility and interoperability — a JOSS review, geopackage import support, deprecation of the SSN-to-SSN2 bridge, marginal means through emmeans. The 2025 releases turn to scale, moving distance matrices onto disk via filematrix and routing estimation and prediction through the local approximation. The 0.4.0 default change is the visible consequence: the neighbourhood size rises from 100 to 200, buying accuracy now that the surrounding machinery can afford it.
◆ Prediction
With the large-data path established and its default just retuned, the next work most likely tightens that approximation further or extends it to the model classes the local argument does not yet cover.
tulpaRatio
0.0ANALYTICS
A Bayesian ratio-modelling package that threw out its Stan dependency and wrote its own sampler
◆ Current state
ratiod models ratios, rates and proportions hierarchically, with the stated position that a ratio is a derived quantity and inference should run on the latent numerator and denominator processes rather than their quotient. The 1.0.0 release shipped a native HMC/NUTS backend, removing the Stan dependency that packages in this space normally take as given. Everything since has been sampler optimisation, benchmarked against the Stan implementations it replaced.
◆ Where it's heading
The feed reads as one architectural bet followed by the work to justify it. After the native backend landed, the releases are a steady march of gradient and adaptation work — hand-coded gradients for more model families, L-BFGS mass matrix adaptation, an O2 build — each measured as a speed multiple against Stan. Coverage is tracked openly as a fraction (48 of 60 hand-coded configs), and unresolved problems are named rather than buried, including a deferred GP spatial bug.
◆ Prediction
The hand-coded gradient coverage count is the visible backlog, so the next releases most likely close the remaining configs and resolve the GP spatial issue that the benchmark release explicitly deferred.
Alternatives to SSN2 and tulpaRatio
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 SSN2 or tulpaRatio.
MetaboAnalystR
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
fmtr
Rebuilding SAS's formatting layer in R, one format specification at a time
betaselectr
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
BiocManager
Bioconductor's installer, frozen at 1.30.x and tuned almost entirely through environment variables
dcurves
Decision curve analysis, settled since 2022 and now moving only when its neighbours do
See all SSN2 alternatives → · See all tulpaRatio alternatives →
Recent activity from SSN2 and tulpaRatio
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agotulpaRatioHand-coded gradients reach binomial zero-inflated and hurdle models
- 6mo agotulpaRatioGaussian process sampling reaches roughly 4x Stan
- 7mo agotulpaRatioL-BFGS mass matrix adaptation for MSGP models
- 7mo agotulpaRatioBenchmarks published for 35 of 40 model configurations
- 7mo agotulpaRatioFirst stable release ships a native HMC/NUTS backend, no Stan required ⚡
- 9mo agoSSN2Local neighbourhood default doubled to 200
- 10mo agoSSN2partition_factor regression fixed, spmodel floor raised
- 0y agoSSN2On-disk distance matrices lift the large-data ceiling
- 1y agoSSN2Numeric stability fix for beta-family models
- 2y agoSSN2Geopackage import support and the JOSS review release
- 2y agoSSN2Snapshot tag marking JOSS acceptance
Frequently asked questions
What is the difference between SSN2 and tulpaRatio?
Both compete on the same themes — spatial-statistics, r-package — within Analytics. SSN2 and tulpaRatio 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 SSN2 better than tulpaRatio?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. SSN2 and tulpaRatio 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 SSN2?
Top SSN2 alternatives in Analytics are ranked by recent ship velocity. Browse the "SSN2 alternatives" section above for the current picks, or visit /alternatives/ssn2 for the full list with editorial commentary on each.
What are the best alternatives to tulpaRatio?
Top tulpaRatio alternatives in Analytics are ranked by recent ship velocity. Browse the "tulpaRatio alternatives" section above for the current picks, or visit /alternatives/tulparatio for the full list with editorial commentary on each.