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Comparison · Infra & APIs

CptNonPar vs stochvol

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

CptNonPar vs stochvol: at a glance

FeatureCptNonParstochvol
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themeschange-point-detection, nonparametric, defaults, preprocessingbayesian-inference, stochastic-volatility, mcmc, rcpp
Last editorial update49m ago2h ago
WebsiteVisit →Visit →

What is CptNonPar?

Nonparametric change point detection swaps p-values for importance scores.

CptNonPar implements nonparametric MOJO change point detection for possibly multivariate, serially dependent data, through single-lag, multi-lag and multiscale entry points. Recent releases concern how results are reported and how data is preprocessed rather than new detection machinery. The underlying method was accepted at Biometrika during the 0.3.0 cycle.

Read the full CptNonPar trajectory →

What is stochvol?

A Bayesian volatility sampler in its maintenance decade, paying for its own speed

stochvol runs MCMC for stochastic volatility models, with a C++ sampler underneath an R interface. Five years of releases in this window contain no new models: the work is compiler and dependency compatibility, CRAN check notes, and a steady trickle of corrections to the sampler itself. Its methodological milestone, the Journal of Statistical Software paper, is recorded in a 2021 tag.

Read the full stochvol trajectory →

CptNonPar vs stochvol: editorial side-by-side

C
CptNonPar
INFRA · APIS
0.0

Nonparametric change point detection swaps p-values for importance scores.

◆ Current state

CptNonPar implements nonparametric MOJO change point detection for possibly multivariate, serially dependent data, through single-lag, multi-lag and multiscale entry points. Recent releases concern how results are reported and how data is preprocessed rather than new detection machinery. The underlying method was accepted at Biometrika during the 0.3.0 cycle.

◆ Where it's heading

The package is tightening the statistical interface it exposes: p-values gave way to importance scores across all three detection functions, manual thresholds became specifiable per lag, and the latest release makes centring and scaling the default preprocessing step. Each change folds a decision the user previously had to make into the package itself.

◆ Prediction

Expect further work on defaults and reporting around the existing MOJO estimators rather than a new detection method.

S
stochvol
INFRA · APIS
0.0

A Bayesian volatility sampler in its maintenance decade, paying for its own speed

◆ Current state

stochvol runs MCMC for stochastic volatility models, with a C++ sampler underneath an R interface. Five years of releases in this window contain no new models: the work is compiler and dependency compatibility, CRAN check notes, and a steady trickle of corrections to the sampler itself. Its methodological milestone, the Journal of Statistical Software paper, is recorded in a 2021 tag.

◆ Where it's heading

This is what a finished computational package looks like. The formula interface arrived at 3.1.0 and nothing has been added since; what changes is the ground underneath — RcppArmadillo major versions, UBSan checks, error-handling conventions moving from Rf_error to Rcpp::stop for correct memory management. The recurring pattern worth watching is that several releases fix real errors in the sampler's proposal distributions, found by users and by CRAN's own instrumented checks rather than by the maintainer.

◆ Prediction

Nothing in these notes suggests new methodology. Expect the next release when RcppArmadillo or a CRAN check flavour forces one, and treat any bug report against the samplers as the more consequential event.

Alternatives to CptNonPar and stochvol

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 CptNonPar or stochvol.

See all CptNonPar alternatives → · See all stochvol alternatives →

Recent activity from CptNonPar and stochvol

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

  1. 5mo agostochvolSampler crash with constant parameters fixed, plus RcppArmadillo 15
  2. 8mo agoCptNonParData centred and scaled by default before detection
  3. 1y agostochvolTwo CRAN check notes cleared
  4. 1y agoCptNonParImportance scores replace p-values; per-lag manual thresholds
  5. 1y agostochvolProposal variance corrected in the centered parameterisation
  6. 2y agoCptNonParPaper link updated for CRAN checks
  7. 2y agostochvolCRAN stochvol 3.2.4
  8. 2y agostochvolRolling-window indexing and inverse gamma prior validation fixed
  9. 3y agoCptNonParDescription field and example cleanups
  10. 3y agostochvolCore C++ sampler routines exported for reuse

Frequently asked questions

What is the difference between CptNonPar and stochvol?

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

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

What are the best alternatives to CptNonPar?

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

What are the best alternatives to stochvol?

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