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reliagrowr vs susier

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

Shared themes:r-package

reliagrowr vs susier: at a glance

Featurereliagrowrsusier
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesreliability-engineering, r-package, repairable-systems, mcpr-package, statistical-genetics, fine-mapping, cpp-bindings
Last editorial update2h ago1h ago
WebsiteVisit →Visit →

What is reliagrowr?

A reliability growth package put its models behind an MCP server for AI assistants to call.

ReliaGrowR fits reliability growth models to failure data — Crow-AMSAA and Duane, with maximum likelihood estimation, confidence bounds, prediction, and reliability demonstration test planning. The last year widened it well past growth curves into repairable systems: parametric non-homogeneous Poisson process fitting with automatic change point detection, non-parametric mean cumulative function estimation, and system exposure calculation. The most recent release adds goodness-of-fit statistics and exposes the package's functions as Model Context Protocol tools.

Read the full reliagrowr trajectory →

What is susier?

Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs

susieR implements the Sum of Single Effects regression model for variable selection and fine-mapping, widely used in statistical genetics. The recent releases are a tight run of correctness work concentrated in one area: null effect trimming. Version 0.15.55 fixed trimming under the Servin-Stephens residual variance method, 0.15.56 fixed it again for non-uniform prior weights fourteen minutes later, 0.15.57 corrected an ELBO null space term for RSS with X and a matrix symmetry check, and 0.15.58 addressed an alpha0/beta0 issue. Version 0.16.0 migrates the C++ bindings from Rcpp to cpp11 with cpp11armadillo.

Read the full susier trajectory →

reliagrowr vs susier: editorial side-by-side

R
reliagrowr
ANALYTICS
0.0

A reliability growth package put its models behind an MCP server for AI assistants to call.

◆ Current state

ReliaGrowR fits reliability growth models to failure data — Crow-AMSAA and Duane, with maximum likelihood estimation, confidence bounds, prediction, and reliability demonstration test planning. The last year widened it well past growth curves into repairable systems: parametric non-homogeneous Poisson process fitting with automatic change point detection, non-parametric mean cumulative function estimation, and system exposure calculation. The most recent release adds goodness-of-fit statistics and exposes the package's functions as Model Context Protocol tools.

◆ Where it's heading

Two arcs run in parallel. The statistical one is a steady march from plotting a growth curve to modelling recurrent failures properly — segmented NHPP models that detect their own change points, Nelson-Aalen estimation, Cramér-von Mises and Kolmogorov-Smirnov statistics for judging the fits. The interface one is newer and more unusual: the package now ships an MCP server, and its sibling plotting package followed with one two weeks later, so this is a deliberate direction across the maintainer's reliability suite rather than a single experiment. Naming and S3 conventions were cleaned up early, which is what made a uniform tool surface plausible later.

◆ Prediction

Given the sibling packages moved to MCP within weeks of each other, the remaining tools in the suite are the obvious next candidates; on the statistical side, goodness-of-fit having just arrived suggests model comparison and selection helpers are the natural follow-on.

S
susier
ANALYTICS
0.0

Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs

◆ Current state

susieR implements the Sum of Single Effects regression model for variable selection and fine-mapping, widely used in statistical genetics. The recent releases are a tight run of correctness work concentrated in one area: null effect trimming. Version 0.15.55 fixed trimming under the Servin-Stephens residual variance method, 0.15.56 fixed it again for non-uniform prior weights fourteen minutes later, 0.15.57 corrected an ELBO null space term for RSS with X and a matrix symmetry check, and 0.15.58 addressed an alpha0/beta0 issue. Version 0.16.0 migrates the C++ bindings from Rcpp to cpp11 with cpp11armadillo.

◆ Where it's heading

The version-number churn understates how narrow this work is — four consecutive releases touching the same trimming and residual-variance machinery suggests one area where the implementation and the intended behavior had drifted apart. The 0.16.0 binding migration is the only structural change, and it is invisible to users while mattering for build portability and long-term maintenance. Development is clearly active, with automated release tooling and dependency bumps flowing through the same stream.

◆ Prediction

With the binding migration just landed, near-term releases are likely to address fallout from it alongside continued fixes in the same trimming and residual-variance code.

Alternatives to reliagrowr and susier

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 reliagrowr or susier.

See all reliagrowr alternatives → · See all susier alternatives →

Recent activity from reliagrowr and susier

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

  1. 2mo agoreliagrowrReliability growth models exposed as MCP tools
  2. 3mo agosusierMigrates C++ bindings from Rcpp to cpp11 and cpp11armadillo
  3. 3mo agosusierFixes alpha0/beta0 handling under Servin-Stephens
  4. 4mo agoreliagrowrRepairable systems analysis arrives: NHPP, MCF, exposure
  5. 4mo agoreliagrowrMaximum likelihood fitting and failure simulation
  6. 4mo agosusierCorrects the null space ELBO term for RSS with X
  7. 5mo agosusierFixes null effect trimming with non-uniform prior weights
  8. 5mo agosusierFixes null effect trimming under Servin-Stephens estimation
  9. 8mo agoreliagrowrReliaGrowR 0.3.2
  10. 9mo agoreliagrowrMore plotting and printing options for RGA and Duane models
  11. 10mo agoreliagrowrS3 methods replace the ad hoc plotting functions

Frequently asked questions

What is the difference between reliagrowr and susier?

Both compete on the same themes — r-package — within Analytics. reliagrowr and susier 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 reliagrowr better than susier?

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

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

What are the best alternatives to susier?

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