tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
A side-by-side editorial comparison of geodist and ggcorrplot — release velocity, themes, recent moves, and the top alternatives to consider.
geodist stays dependency-free and fast, and warns you when 'cheap' distances stop being honest.
geodist computes geodesic distances between coordinate pairs in C with no dependencies, offering several measures that trade accuracy for speed — including a 'cheap' approximation used by default. The API is small and largely finished; 0.1.0 added geodist_min() for nearest-match lookups and 0.1.1 is a compiler warning fix.
ggcorrplot came back after four years and found its significance markers had been lying
ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.
geodist computes geodesic distances between coordinate pairs in C with no dependencies, offering several measures that trade accuracy for speed — including a 'cheap' approximation used by default. The API is small and largely finished; 0.1.0 added geodist_min() for nearest-match lookups and 0.1.1 is a compiler warning fix.
Development has been about making the speed-accuracy trade visible rather than hiding it. The 0.0.6 release added messages telling users to pick a different measure once the default cheap approximation is applied beyond 100km, where its error stops being negligible. Around that, the work is input handling — tibble support, better lon/lat column matching, vector inputs — and hardening the C code. It is a package that treats being small and correct as the feature.
Expect continued low-frequency maintenance: compiler warnings and geodesic source updates account for three of the last six releases, and the function surface has grown by only two entries in five years.
ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.
Both releases chase the same target: parity with the older corrplot package inside a ggplot2 object. Significance stars appended to coefficient labels, circle scaling, decimal control, then boxed cells and glyphs sized by absolute correlation — these are corrplot's visual vocabulary reimplemented where they can be composed with other ggplot2 layers. The bug fixes point the other way, at foundations: p-values matched to cells by name rather than row position, clustering computed on the unrounded matrix, tl.col actually applied.
With the corrplot look largely reproduced and the correctness backlog cleared, the remaining gap is the mixed upper/lower display corrplot supports; that is the natural next argument if the current release pace holds.
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 geodist or ggcorrplot.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
A single-purpose ggplot2 inset tool, refining the same three arguments.
An R symbolic-maths binding whose changelog is really the C++ core's release notes.
gtfstools stopped guarding its own object model and started accepting everyone else's.
The glue package that makes R carry units and uncertainty through the same calculation.
See all geodist alternatives → · See all ggcorrplot alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ggcorrplot is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. ggcorrplot is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top geodist alternatives in Analytics are ranked by recent ship velocity. Browse the "geodist alternatives" section above for the current picks, or visit /alternatives/geodist-r for the full list with editorial commentary on each.
Top ggcorrplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggcorrplot alternatives" section above for the current picks, or visit /alternatives/ggcorrplot for the full list with editorial commentary on each.