trackeR
Fitness-tracking analysis in slow maintenance, still absorbing upstream breakage.
A side-by-side editorial comparison of midr and PINstimation — release velocity, themes, recent moves, and the top alternatives to consider.
A black-box interpreter reaches CRAN, then learns multi-class and survival responses
midr explains black-box models by fitting an interpretable surrogate through Maximum Interpretation Decomposition — main effects plus second-order interactions, with exact Shapley values for the surrogate. Two months after its first CRAN release it can take a matrix response, which covers multi-class classification and survival models, and hold collections of fitted interpretations in midlist and midrib objects for comparison.
A market-microstructure toolkit that keeps adding estimators as the papers land.
PINstimation estimates probability-of-informed-trading models — PIN, multilayer PIN, adjusted PIN and VPIN — from trade and quote data, and handles the trade classification and aggregation that feeds them. The current 0.2.0 adds ivpin(), a maximum-likelihood variant of VPIN from Ke and Lin (2017). The package's early history is compressed into a single hour of backfilled tags in October 2022, so version order there does not track release order.
midr explains black-box models by fitting an interpretable surrogate through Maximum Interpretation Decomposition — main effects plus second-order interactions, with exact Shapley values for the surrogate. Two months after its first CRAN release it can take a matrix response, which covers multi-class classification and survival models, and hold collections of fitted interpretations in midlist and midrib objects for comparison.
The releases move outward along two axes at once: what can be interpreted, and how much of it fits in memory. Version 0.5.3 rebuilt the fitting path to avoid materialising large design matrices and added a save.memory option; 0.6.0 widened the response from a vector to a matrix and added parametric link functions. Class and argument names were shortened in the same release, so the package is still willing to break itself this early.
With multiple models now held in one object and visualisation methods for them, comparison across models is the surface most likely to fill out next — the collection classes exist but the notes describe manipulation and plotting rather than any comparison metric.
PINstimation estimates probability-of-informed-trading models — PIN, multilayer PIN, adjusted PIN and VPIN — from trade and quote data, and handles the trade classification and aggregation that feeds them. The current 0.2.0 adds ivpin(), a maximum-likelihood variant of VPIN from Ke and Lin (2017). The package's early history is compressed into a single hour of backfilled tags in October 2022, so version order there does not track release order.
Each release tracks the literature: a Bayesian PIN estimator from Griffin et al., an improved VPIN from Ke and Lin, initial-parameter generation realigned to Ersan and Ghachem. The other steady thread is data handling — matrix inputs so the estimators compose with rolling windows, user-specified aggregation frequencies, and now quote leads as well as lags. The three-year gap between 0.1.2 and 0.2.0 makes this a slow, publication-paced package rather than an actively developed one.
On this pattern the next release adds whatever estimator the authors publish next, since two of the three feature releases here implement a specific paper. Nothing in the entries points to a change in the package's structure.
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 midr or PINstimation.
Fitness-tracking analysis in slow maintenance, still absorbing upstream breakage.
State-panel tooling holding steady since its 2020 data and ergonomics release.
Five years of compiler and CRAN fixes on a capture-recapture package.
A first release that turns meta-analytic heterogeneity into interpretable subgroups.
A meta-analysis toolkit still renaming its own API as it adds effect sizes.
Recurrent-event modelling settles, with mean_no() promoted to stable.
See all midr alternatives → · See all PINstimation alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. midr and PINstimation 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. midr and PINstimation 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.
Top midr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "midr alternatives" section above for the current picks, or visit /alternatives/midr for the full list with editorial commentary on each.
Top PINstimation alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "PINstimation alternatives" section above for the current picks, or visit /alternatives/pinstimation for the full list with editorial commentary on each.