bsvarSIGNs
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
A side-by-side editorial comparison of BayesianMCPMod and HydroPortailStats — release velocity, themes, recent moves, and the top alternatives to consider.
A Bayesian dose-finding package extends from continuous endpoints to binary ones
BayesianMCPMod implements the Bayesian form of MCP-Mod for dose-finding trials, combining a multiple-comparison test for dose-response signal with model fitting for dose selection. Version 1.3.0 added functions and vignettes for the binary endpoint case, opening the package beyond the continuous endpoints it was built around, and 1.3.2 followed with Firth's penalized regression to handle separation in those binary fits. The same 1.3.0 release let assessDesign() accept custom simulated data and custom model estimates, which moves simulation control out of the package and into the user's hands.
France's national flood statistics, ported out of Fortran and into R.
HydroPortailStats exposes the statistical machinery behind the French HydroPortail — distribution fitting, quantile curves and their uncertainties for hydrological series. The 2025 release re-implements the HBay Fortran executable in R, adding Bayesian estimation from historical flood records with censored and interval-valued data and systematic measurement error, plus a triangular distribution and truncated random generation.
BayesianMCPMod implements the Bayesian form of MCP-Mod for dose-finding trials, combining a multiple-comparison test for dose-response signal with model fitting for dose selection. Version 1.3.0 added functions and vignettes for the binary endpoint case, opening the package beyond the continuous endpoints it was built around, and 1.3.2 followed with Firth's penalized regression to handle separation in those binary fits. The same 1.3.0 release let assessDesign() accept custom simulated data and custom model estimates, which moves simulation control out of the package and into the user's hands.
Each release has widened the estimands and data shapes the framework accepts rather than changing its statistical core. 1.0.2 added non-monotonic beta and quadratic model shapes; 1.1.0 introduced getMED() for the minimally efficacious dose and parallel execution through the future framework; 1.2.0 switched the posterior and contrast functions from a standard deviation vector to a full covariance matrix and supported non-zero off-diagonals in the MCP step. The binary endpoint work is the same pattern applied to the outcome type, and the Firth addition shows the follow-through of a maintainer who has hit the separation problem in practice.
Expect the binary endpoint arm to keep filling in - more diagnostics and design assessment coverage matching what the continuous case already has - since 1.3.2 addressed a specific estimation failure rather than adding a new capability.
HydroPortailStats exposes the statistical machinery behind the French HydroPortail — distribution fitting, quantile curves and their uncertainties for hydrological series. The 2025 release re-implements the HBay Fortran executable in R, adding Bayesian estimation from historical flood records with censored and interval-valued data and systematic measurement error, plus a triangular distribution and truncated random generation.
The package started as a straight extraction of the portal's existing functions and is now absorbing the surrounding legacy toolchain: HBay was a separate compiled program with its own config files, and this release brings both the method and its configuration format inside R. Releases are sparse — three in two years, with an eighteen-month gap before the latest — and the intervening one was CRAN paperwork.
The HBay import came with a configuration-file reader for continuity with the old executable, which suggests further legacy hydrological tooling could follow the same path; the entries name no specific next target.
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 BayesianMCPMod or HydroPortailStats.
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
Fast design-based estimators for experiments, coasting on CRAN patches.
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
IP address vectors for R that hit 1.0 and then went quiet.
A column-key toolkit for stitching decades of ecological field data into one table.
Microsoft's automated forecasting framework, still mostly a one-maintainer effort.
See all BayesianMCPMod alternatives → · See all HydroPortailStats alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — bayesian-statistics, r-package — within Infra & APIs. BayesianMCPMod and HydroPortailStats 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. BayesianMCPMod and HydroPortailStats 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.
Top BayesianMCPMod alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "BayesianMCPMod alternatives" section above for the current picks, or visit /alternatives/bayesianmcpmod for the full list with editorial commentary on each.
Top HydroPortailStats alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "HydroPortailStats alternatives" section above for the current picks, or visit /alternatives/hydroportailstats for the full list with editorial commentary on each.