rjdqa
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
A side-by-side editorial comparison of NWCTrends and survminer — release velocity, themes, recent moves, and the top alternatives to consider.
The salmon status-review trend package, maintained one federal review cycle at a time
NWCTrends fits multivariate state-space trend models to Pacific salmon population data and generates the tables and figures used in NOAA Northwest Fisheries Science Center viability and status reviews. Its release history maps onto those review cycles rather than a development calendar: v1.0 carries the 2015 review code, v1.25 the 2020 review, v1.30 the changes since. The 2026 v1.31 is internal restructuring and a dependency swap.
survminer is back after a five-year gap, and spending it cutting dependencies loose.
survminer draws Kaplan-Meier curves and Cox diagnostics on top of ggplot2, and it sits under a large share of published survival figures. After a long dormancy it has shipped three releases since late 2024, and all of them are about staying compatible: with ggplot2 3.5, then 4.0, and now without survMisc, whose weighted log-rank tests are computed internally in base R as of 0.5.2. The plotting API itself has not changed.
NWCTrends fits multivariate state-space trend models to Pacific salmon population data and generates the tables and figures used in NOAA Northwest Fisheries Science Center viability and status reviews. Its release history maps onto those review cycles rather than a development calendar: v1.0 carries the 2015 review code, v1.25 the 2020 review, v1.30 the changes since. The 2026 v1.31 is internal restructuring and a dependency swap.
Development is driven by reproducibility of a specific government reporting product, so most work goes into making the report generation configurable and the fitting assumptions explicit rather than into new modelling. The 2020 cycle removed hard-coded per-population hacks and made the fitting window an explicit argument; the 2023 cycle moved plot styling into package options and clarified how missing data and zeros are handled in the published tables.
The cadence suggests the next substantive release arrives with the next status review rather than before it, most likely continuing the move of report parameters out of function signatures and into structured configuration.
survminer draws Kaplan-Meier curves and Cox diagnostics on top of ggplot2, and it sits under a large share of published survival figures. After a long dormancy it has shipped three releases since late 2024, and all of them are about staying compatible: with ggplot2 3.5, then 4.0, and now without survMisc, whose weighted log-rank tests are computed internally in base R as of 0.5.2. The plotting API itself has not changed.
This is a revival by maintenance, not by feature work — the same pattern as its sibling packages from the same author. The dependency surface is being reduced rather than extended, and each release absorbs a breaking change from ggplot2 that would otherwise leave existing scripts producing errors or misaligned risk tables. Compatibility fixes now arrive within months of the upstream change rather than years.
Continued ggplot2 4.x tracking is the most likely next release content, since 0.5.2 already carries fixes for 4.0.x aesthetics and the GeomConfint stairstep problem.
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 NWCTrends or survminer.
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series
A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release
A statistician's personal toolbox, growing one plotting utility at a time
R/qtl is in pure custodial mode: every recent release answers a compiler, not a user
See all NWCTrends alternatives → · See all survminer alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. NWCTrends and survminer 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. NWCTrends and survminer 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.
Top NWCTrends alternatives in Analytics are ranked by recent ship velocity. Browse the "NWCTrends alternatives" section above for the current picks, or visit /alternatives/nwctrends-r for the full list with editorial commentary on each.
Top survminer alternatives in Analytics are ranked by recent ship velocity. Browse the "survminer alternatives" section above for the current picks, or visit /alternatives/survminer for the full list with editorial commentary on each.