← Back to home
Comparison · Analytics

reliagrowr vs reliaplotr

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

Shared themes:reliability-engineeringr-packagemcpai-tooling

reliagrowr vs reliaplotr: at a glance

Featurereliagrowrreliaplotr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesreliability-engineering, r-package, repairable-systems, mcpreliability-engineering, r-package, plotly, mcp
Last editorial update1d ago1d 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 reliaplotr?

The Weibull plotting package renamed itself, then handed its charts to AI assistants.

ReliaPlotR draws interactive reliability plots with plotly — probability plots, contour plots, Duane and reliability growth charts, accelerated life testing plots by stress level, mean cumulative function curves for repairable systems, and exposure plots. It was WeibullR.plotly until late 2025, and the rename tracked a real widening of scope rather than just a label change. The current release adds tidy extractors that turn fitted model objects into data frames, and an MCP server exposing five of its fit and plot functions as tools.

Read the full reliaplotr trajectory →

reliagrowr vs reliaplotr: 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.

R
reliaplotr
ANALYTICS
0.0

The Weibull plotting package renamed itself, then handed its charts to AI assistants.

◆ Current state

ReliaPlotR draws interactive reliability plots with plotly — probability plots, contour plots, Duane and reliability growth charts, accelerated life testing plots by stress level, mean cumulative function curves for repairable systems, and exposure plots. It was WeibullR.plotly until late 2025, and the rename tracked a real widening of scope rather than just a label change. The current release adds tidy extractors that turn fitted model objects into data frames, and an MCP server exposing five of its fit and plot functions as tools.

◆ Where it's heading

The package has been following its analysis siblings function for function: as accelerated life testing and repairable systems modelling landed in the wider suite, the matching plot types appeared here, and when the growth-analysis package shipped an MCP server, this one followed two weeks later. The tidy extractors point the same way — a plotting package that can also return parameter estimates, goodness-of-fit metrics, and confidence bounds as tidy frames is one designed to be consumed programmatically, by a pipeline or an assistant, not only read on screen. Overlaying multiple model fits on a single plot has been a recurring request answered across several releases.

◆ Prediction

Expect the tidy extractor and MCP tool surfaces to keep expanding together, since each new plot type in the suite now implies both a chart and a machine-readable version of what it shows.

Alternatives to reliagrowr and reliaplotr

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 reliaplotr.

See all reliagrowr alternatives → · See all reliaplotr alternatives →

Recent activity from reliagrowr and reliaplotr

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

  1. 2mo agoreliaplotrTidy model extractors plus five plotting tools over MCP
  2. 2mo agoreliaplotrNHPP plots switch to the mean cumulative function
  3. 2mo agoreliagrowrReliability growth models exposed as MCP tools
  4. 4mo agoreliaplotrAccelerated life testing and repairable systems plots added
  5. 4mo agoreliagrowrRepairable systems analysis arrives: NHPP, MCF, exposure
  6. 4mo agoreliagrowrMaximum likelihood fitting and failure simulation
  7. 8mo agoreliaplotrDuane plots gain confidence bounds
  8. 8mo agoreliagrowrReliaGrowR 0.3.2
  9. 9mo agoreliagrowrMore plotting and printing options for RGA and Duane models
  10. 10mo agoreliaplotrReliaPlotR v0.4.1
  11. 10mo agoreliaplotrRenamed from WeibullR.plotly to ReliaPlotR
  12. 11mo agoreliagrowrS3 methods replace the ad hoc plotting functions

Frequently asked questions

What is the difference between reliagrowr and reliaplotr?

Both compete on the same themes — reliability-engineering, r-package, mcp, ai-tooling — within Analytics. reliagrowr and reliaplotr 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 reliaplotr?

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

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