STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
intsurv vs TidyDensity
A side-by-side editorial comparison of intsurv and TidyDensity — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
intsurv vs TidyDensity: 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 TidyDensity?
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.
intsurv vs TidyDensity: 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.
TidyDensity
0.0ANALYTICS
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
◆ Current state
TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.
◆ Where it's heading
The package is filling out a matrix rather than changing shape — every new distribution gets the same four or five companion functions, so the surface grows predictably and the design does not. What variation exists comes from utilities that work across distributions: MCMC sampling, bootstrap helpers, time series conversion, distribution comparison. The two genuine breaking changes in this window were both internal reworks, moving generation onto data.table and rewriting quantile normalization for speed.
◆ Prediction
The established pattern of adding a distribution with its full helper set is the most likely continuation. Recent releases have been small, suggesting the catalogue is approaching the distributions its author considers worth covering.
Alternatives to intsurv and TidyDensity
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 TidyDensity.
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.
See all intsurv alternatives → · See all TidyDensity alternatives →
Recent activity from intsurv and TidyDensity
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10mo agointsurvModel configuration moves into dedicated control functions
- 11mo agoTidyDensityquantile_normalize rewritten, changing its output
- 1y agoTidyDensityDocumentation corrections for two distribution functions
- 2y agoTidyDensityZero-truncated distributions and AIC helpers added in bulk
- 2y agoTidyDensityMCMC sampling and quantile normalization join the utilities
- 2y agoTidyDensityGeneration moves to data.table; native pipe raises the R floor
- 2y agoTidyDensityDistributions convertible to time series objects
- 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 TidyDensity?
Both compete on the same themes — r-package — within Analytics. intsurv and TidyDensity 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 TidyDensity?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. intsurv and TidyDensity 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 TidyDensity?
Top TidyDensity alternatives in Analytics are ranked by recent ship velocity. Browse the "TidyDensity alternatives" section above for the current picks, or visit /alternatives/tidydensity for the full list with editorial commentary on each.