fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
Comparison · Analytics
detectseparation vs tglkmeans
A side-by-side editorial comparison of detectseparation and tglkmeans — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
detectseparation vs tglkmeans: at a glance
What is detectseparation?
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
detectseparation identifies separation and infinite estimates in binomial-response GLMs — the condition where maximum likelihood estimates diverge and standard software reports large coefficients with enormous standard errors instead of an error. Version 0.3 was the structural turn: detect_infinite_estimates() became the general method covering log, logit, probit and cauchit links, with detect_separation() demoted to a wrapper around it. Version 0.4 in April 2026 adds the ability to distinguish complete from quasi-complete separation via separation_type.
What is tglkmeans?
A k-means implementation that just told users their Spearman clustering on missing data was wrong
tglkmeans is a multi-core k-means implementation with seeding, aimed at single-cell and other large matrix workloads. Version 0.4.0 flipped the id_column default and moved to R's random number generator, 0.5.x added count-matrix downsampling and fixed id handling, and 0.6.3 in May 2026 is a correctness release: Spearman distance was ranking missing values as the largest value instead of dropping them, and predict_tgl_kmeans() with Euclidean distance did not reproduce the training metric when a cluster center had a missing dimension.
detectseparation vs tglkmeans: editorial side-by-side
detectseparation
0.0ANALYTICS
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
◆ Current state
detectseparation identifies separation and infinite estimates in binomial-response GLMs — the condition where maximum likelihood estimates diverge and standard software reports large coefficients with enormous standard errors instead of an error. Version 0.3 was the structural turn: detect_infinite_estimates() became the general method covering log, logit, probit and cauchit links, with detect_separation() demoted to a wrapper around it. Version 0.4 in April 2026 adds the ability to distinguish complete from quasi-complete separation via separation_type.
◆ Where it's heading
The package has been generalizing steadily — first past its own framing, since separation is one case of infinite estimates rather than the whole problem, and now toward finer classification of what it detects. The distinction 0.4 adds is practically useful because complete and quasi-complete separation call for different responses. Release intervals are long, roughly two to four years, which fits a diagnostic tool whose underlying theory is settled.
◆ Prediction
With link coverage broad and separation now classified by type, further work is more likely to refine reporting than to extend detection to new model families.
tglkmeans
0.0ANALYTICS
A k-means implementation that just told users their Spearman clustering on missing data was wrong
◆ Current state
tglkmeans is a multi-core k-means implementation with seeding, aimed at single-cell and other large matrix workloads. Version 0.4.0 flipped the id_column default and moved to R's random number generator, 0.5.x added count-matrix downsampling and fixed id handling, and 0.6.3 in May 2026 is a correctness release: Spearman distance was ranking missing values as the largest value instead of dropping them, and predict_tgl_kmeans() with Euclidean distance did not reproduce the training metric when a cluster center had a missing dimension.
◆ Where it's heading
The package handles missing data across three distance metrics, and 0.6.3 shows those paths had drifted apart — Spearman behaved unlike Euclidean and Pearson, and prediction behaved unlike training. Both fixes change results on affected data, and the release notes are careful to bound exactly where: Spearman on data with NAs changes, complete data does not. Performance work runs alongside, with the dense per-thread vote matrix removed from the reassignment step.
◆ Prediction
With the metric paths now aligned on missing-value handling, further work is more likely to target the parallel reassignment internals than the distance semantics.
Alternatives to detectseparation and tglkmeans
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 detectseparation or tglkmeans.
gcube
gcube's recent releases are all packaging metadata, not simulation code
cubist
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats
ggstats keeps widening what a coefficient or Likert plot can be
ecodive
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
simStateSpace
State-space data simulation for R, filled in one function at a time
See all detectseparation alternatives → · See all tglkmeans alternatives →
Recent activity from detectseparation and tglkmeans
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agotglkmeansSpearman metric no longer ranks missing values as the largest
- 3mo agodetectseparationdetectseparation v0.4
- 2y agotglkmeansFixes corrupted cluster ids and dropped dimnames
- 2y agotglkmeansAdds downsample_matrix() for count matrices
- 2y agotglkmeansBreaking: id_column defaults to FALSE, switches to R's RNG
- 3y agodetectseparationdetectseparation v0.3
- 5y agodetectseparationdetectseparation v0.2
Frequently asked questions
What is the difference between detectseparation and tglkmeans?
Both compete on the same themes — r-package — within Analytics. detectseparation and tglkmeans 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 detectseparation better than tglkmeans?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. detectseparation and tglkmeans 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 detectseparation?
Top detectseparation alternatives in Analytics are ranked by recent ship velocity. Browse the "detectseparation alternatives" section above for the current picks, or visit /alternatives/detectseparation for the full list with editorial commentary on each.
What are the best alternatives to tglkmeans?
Top tglkmeans alternatives in Analytics are ranked by recent ship velocity. Browse the "tglkmeans alternatives" section above for the current picks, or visit /alternatives/tglkmeans for the full list with editorial commentary on each.