STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
intsurv vs mev
A side-by-side editorial comparison of intsurv and mev — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
intsurv vs mev: at a glance
What is intsurv?
A Cox cure-rate model package woke up after four years to simplify its own interface.
intsurv fits Cox cure rate models for right-censored survival data where event status may be uncertain — the case where you cannot tell whether a subject experienced the event or was never susceptible to it. The core has been stable since 2019: cox_cure() and its regularized counterpart cox_cure_net(), plus a weighted concordance index and a data simulator. After more than four years without a release, version 0.3.0 arrived in September 2025 and restructured how those two functions are configured rather than adding capability.
What is mev?
An extreme-value toolkit reorganised its whole API into prefixed families and tripled its estimator count.
mev provides likelihood-based inference for univariate and multivariate extreme value models — threshold selection, shape estimation, tail dependence and max-stable simulation. Version 2.0 was a deliberate reorganisation: every threshold-selection routine now carries a thselect. prefix, every stability plot a tstab. prefix, and every extremal-dependence measure an xdep. prefix, with the old names deprecated but mostly still working. The same release added a large batch of estimators — Stein-weighted GPD, roughly a dozen shape estimators, second-order regular variation, L-moment GPD and Weissman quantiles.
intsurv vs mev: editorial side-by-side
intsurv
0.0ANALYTICS
A Cox cure-rate model package woke up after four years to simplify its own interface.
◆ Current state
intsurv fits Cox cure rate models for right-censored survival data where event status may be uncertain — the case where you cannot tell whether a subject experienced the event or was never susceptible to it. The core has been stable since 2019: cox_cure() and its regularized counterpart cox_cure_net(), plus a weighted concordance index and a data simulator. After more than four years without a release, version 0.3.0 arrived in September 2025 and restructured how those two functions are configured rather than adding capability.
◆ Where it's heading
The package has reached the point where the methods are settled and the remaining work is ergonomics. Moving control parameters, M-step settings and penalty specification into cox_cure.control(), cox_cure.mstep() and cox_cure_net.penalty() follows the established R convention of separating tuning from the model formula, and it arrives long after the arguments accumulated. The C++ headers were placed in inst/include as early as 2019 so other packages could link against them, which suggests the implementation was always intended to be reused.
◆ Prediction
The gap between 0.2.2 and 0.3.0 makes cadence a poor basis for prediction. What the entries do support is that the interface rework is unfinished business rather than a prelude to new methods, so consolidation around the new helper functions is the likelier next step.
mev
0.0ANALYTICS
An extreme-value toolkit reorganised its whole API into prefixed families and tripled its estimator count.
◆ Current state
mev provides likelihood-based inference for univariate and multivariate extreme value models — threshold selection, shape estimation, tail dependence and max-stable simulation. Version 2.0 was a deliberate reorganisation: every threshold-selection routine now carries a thselect. prefix, every stability plot a tstab. prefix, and every extremal-dependence measure an xdep. prefix, with the old names deprecated but mostly still working. The same release added a large batch of estimators — Stein-weighted GPD, roughly a dozen shape estimators, second-order regular variation, L-moment GPD and Weissman quantiles.
◆ Where it's heading
The package is consolidating into a reference implementation of the extreme-value literature rather than a collection of one-off routines. Sixteen threshold-selection methods now share standardised arguments and their own plot and print methods with automatic selection, which is the tell: the goal is comparability across methods, not just availability. Dependency reduction runs alongside, with distribution functions written in-package to drop evd and Rsolnp replacing nloptr in earlier releases.
◆ Prediction
Version 2.1 continued adding threshold-selection routines within the new naming scheme, so the next release most likely follows the same pattern — more estimators fitted to the established prefixes, plus fixes to the 2.0 renaming. The entries give no sign of a further structural change.
Alternatives to intsurv and mev
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 intsurv or mev.
ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
kde1d
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
svines
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
gghighlight
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
rtrek
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
Recent activity from intsurv and mev
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 9mo agomevTwo more threshold-selection routines slot into the new scheme
- 9mo agomevThreshold, stability and dependence functions regrouped under prefixes ⚡
- 10mo agointsurvModel configuration moves into dedicated control functions
- 2y agomevBoundary-case likelihood fixes, bundled with the prior release's notes
- 3y agomevGEV and GP distribution functions brought in-house to drop evd
- 4y agomevFour max-stable families, fixed parameters and threshold diagnostics
- 5y agointsurvCross-validated model selection and offset terms added
- 6y agointsurvC++ headers relocated so other packages can link them
- 7y agointsurvCox cure models for uncertain event status arrive
- 7y agointsurvParameter initialization methods added to the alpha
- 7y agointsurvAlpha cut for paper submission and simulation reproducibility
Frequently asked questions
What is the difference between intsurv and mev?
Both compete on the same themes — r-package — within Analytics. intsurv and mev 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 intsurv better than mev?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. intsurv and mev 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 intsurv?
Top intsurv alternatives in Analytics are ranked by recent ship velocity. Browse the "intsurv alternatives" section above for the current picks, or visit /alternatives/intsurv for the full list with editorial commentary on each.
What are the best alternatives to mev?
Top mev alternatives in Analytics are ranked by recent ship velocity. Browse the "mev alternatives" section above for the current picks, or visit /alternatives/mev for the full list with editorial commentary on each.