← Back to home
Comparison · Analytics

SimInf vs xts

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

SimInf vs xts: at a glance

FeatureSimInfxts
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesepidemiology, stochastic-simulation, bayesian-inference, r-packager, time-series, finance, c-api
Last editorial update1h ago2h ago
WebsiteVisit →Visit →

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 →

What is xts?

xts is finished software, and its releases now track R's C API more than user requests.

xts is the time-series class underpinning much of R's financial stack, and it behaves like infrastructure: the visible releases are bug fixes, plotting repairs and conformance work. A recurring thread is removing calls R no longer considers public — SET_TYPEOF in 0.14.0 and 0.14.1, then ATTRIB() and SET_ATTRIB() in 0.14.2. Feature additions are rare and small, the last cluster being open-ended time-of-day subsetting and na.fill performance in 0.13.0.

Read the full xts trajectory →

SimInf vs xts: editorial side-by-side

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.

X
xts
ANALYTICS
0.0

xts is finished software, and its releases now track R's C API more than user requests.

◆ Current state

xts is the time-series class underpinning much of R's financial stack, and it behaves like infrastructure: the visible releases are bug fixes, plotting repairs and conformance work. A recurring thread is removing calls R no longer considers public — SET_TYPEOF in 0.14.0 and 0.14.1, then ATTRIB() and SET_ATTRIB() in 0.14.2. Feature additions are rare and small, the last cluster being open-ended time-of-day subsetting and na.fill performance in 0.13.0.

◆ Where it's heading

Two forces drive releases. R core keeps narrowing its public C API, and xts keeps rewriting internals to stay inside it; separately, ggplot-era changes elsewhere in the ecosystem surface plotting bugs that get fixed one report at a time. Nearly every entry credits an outside reporter, which is what maintenance of a dependency this widely used looks like.

◆ Prediction

Further C API conformance work is the safest expectation, since two consecutive releases have each removed a different non-API entry point and R has continued tightening that boundary.

Alternatives to SimInf and xts

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 SimInf or xts.

See all SimInf alternatives → · See all xts alternatives →

Recent activity from SimInf and xts

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

  1. 5mo agoxtsmulti.panel plots beyond 8 columns; SET_TYPEOF removed from C
  2. 5mo agoxtsATTRIB removed from C; rollapply.xts accepts vector widths
  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 agoxtsMulti-panel event lines; first SET_TYPEOF replacement
  7. 2y agoxtstclass changes now alter index values; log-scale y-axis added
  8. 2y agoSimInfModel parser gains variables and enumeration constants
  9. 2y agoSimInfindividual_events() added for raw event data cleaning
  10. 3y agoxtsUpdate path for pre-0.12 objects missing index attributes
  11. 3y agoxtsOpen-ended time-of-day subsetting; fast scalar na.fill
  12. 3y agoSimInfConfigure script uses R to locate the compiler

Frequently asked questions

What is the difference between SimInf and xts?

They serve adjacent needs but don't currently overlap on shipped themes. SimInf and xts 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 SimInf better than xts?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. SimInf and xts 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 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.

What are the best alternatives to xts?

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