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Comparison · Analytics

ggcorrplot vs SimInf

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

ggcorrplot vs SimInf: at a glance

FeatureggcorrplotSimInf
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themescorrelation, r, ggplot2, visualizationepidemiology, stochastic-simulation, bayesian-inference, r-package
Last editorial update6h ago51m ago
WebsiteVisit →Visit →

What is ggcorrplot?

ggcorrplot came back after four years and found its significance markers had been lying

ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.

Read the full ggcorrplot trajectory →

What is SimInf?

SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series

SimInf simulates stochastic disease spread over networks of nodes, with a model parser that compiles user-specified transitions to C. Version 10.0.0 was a deliberate major break: the SimInf_pfilter S4 class and the bootstrap filtering interface were redesigned, a replicates slot was added to SimInf_model, a multi-particle variant of the split-step solver arrived, and the package gained Particle Markov Chain Monte Carlo fitting against observed time series. The follow-up 10.1.0 is a single zero-length memcpy fix found by CRAN's M1 checks.

Read the full SimInf trajectory →

ggcorrplot vs SimInf: editorial side-by-side

G
ggcorrplot
ANALYTICS
2.5

ggcorrplot came back after four years and found its significance markers had been lying

◆ Current state

ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.

◆ Where it's heading

Both releases chase the same target: parity with the older corrplot package inside a ggplot2 object. Significance stars appended to coefficient labels, circle scaling, decimal control, then boxed cells and glyphs sized by absolute correlation — these are corrplot's visual vocabulary reimplemented where they can be composed with other ggplot2 layers. The bug fixes point the other way, at foundations: p-values matched to cells by name rather than row position, clustering computed on the unrounded matrix, tl.col actually applied.

◆ Prediction

With the corrplot look largely reproduced and the correctness backlog cleared, the remaining gap is the mixed upper/lower display corrplot supports; that is the natural next argument if the current release pace holds.

S
SimInf
ANALYTICS
0.0

SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series

◆ Current state

SimInf simulates stochastic disease spread over networks of nodes, with a model parser that compiles user-specified transitions to C. Version 10.0.0 was a deliberate major break: the SimInf_pfilter S4 class and the bootstrap filtering interface were redesigned, a replicates slot was added to SimInf_model, a multi-particle variant of the split-step solver arrived, and the package gained Particle Markov Chain Monte Carlo fitting against observed time series. The follow-up 10.1.0 is a single zero-length memcpy fix found by CRAN's M1 checks.

◆ Where it's heading

The package has been moving from simulation toward inference for several releases. The 9.x line built the input side — utilities for cleaning raw individual event data, variables and enumeration constants in the model parser — and 10.0.0 closed the loop by making the simulator fittable to data through PMCMC. The version number was incremented precisely because that required breaking the particle filter interface.

◆ Prediction

Fitting machinery this new usually needs a second pass on usability, so the next releases most likely focus on diagnostics and documentation around PMCMC rather than on the simulation core, which has been stable across the whole 9.x and 10.x history.

Alternatives to ggcorrplot and SimInf

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 ggcorrplot or SimInf.

See all ggcorrplot alternatives → · See all SimInf alternatives →

Recent activity from ggcorrplot and SimInf

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

  1. 21d agoggcorrplotggcorrplot 0.3.0 adds boxed cells and correlation-sized squares
  2. 1mo agoggcorrplotggcorrplot 0.2.0 fixes significance markers broken by hc.order
  3. 9mo agoSimInfAvoid memcpy on zero-length continuous state vector
  4. 9mo agoSimInfPMCMC fitting arrives; particle filter interface redesigned
  5. 2y agoSimInfDocumentation link anchors; parser dependency fix
  6. 2y agoSimInfModel parser gains variables and enumeration constants
  7. 2y agoSimInfindividual_events() added for raw event data cleaning
  8. 3y agoSimInfConfigure script uses R to locate the compiler
  9. 3y agoggcorrplotggcorrplot 0.1.4
  10. 6y agoggcorrplotggcorrplot 0.1.3
  11. 7y agoggcorrplotggcorrplot 0.1.2
  12. 10y agoggcorrplotggcorrplot's first release: correlograms in ggplot2

Frequently asked questions

What is the difference between ggcorrplot and SimInf?

They serve adjacent needs but don't currently overlap on shipped themes. ggcorrplot is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is ggcorrplot better than SimInf?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggcorrplot is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to ggcorrplot?

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

What are the best alternatives to SimInf?

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