PurpleAir
The R client for PurpleAir sensors keeps finding its time-averaging was wrong.
Comparison · Analytics
glmbayes vs lstar
A side-by-side editorial comparison of glmbayes and lstar — release velocity, themes, recent moves, and the top alternatives to consider.
glmbayes vs lstar: at a glance
What is glmbayes?
A GPU-accelerated Bayesian GLM package buys its way into the standard R Bayesian toolchain
glmbayes fits Bayesian generalized linear models with optional OpenCL acceleration. The last four months moved it from a package with its own vocabulary to one that answers the insight and bayestestR generics the rest of the R Bayesian ecosystem is built on, while pushing the OpenCL kernels out into a separate nmathopencl dependency that carries CRAN Windows binaries. It returned to CRAN in August after an archival over a configure policy issue.
What is lstar?
A single-cell data store commits to Zarr v3 and range-readable hosting across four language surfaces
lstar stores single-cell data behind one C++ core with Python, R and JS/WASM bindings, and ships a browser viewer that reads the store directly. Zarr v3 is now the default on-disk format across all four surfaces, with zstd compression and sharding that packs many chunks into fewer objects. Viewer stores are compressed per field and resolved at chunk granularity, so a hosted viewer fetches only what it displays. The tag stream carries both lstar and lstar-sc releases.
glmbayes vs lstar: editorial side-by-side
glmbayes
6.3ANALYTICS
A GPU-accelerated Bayesian GLM package buys its way into the standard R Bayesian toolchain
◆ Current state
glmbayes fits Bayesian generalized linear models with optional OpenCL acceleration. The last four months moved it from a package with its own vocabulary to one that answers the insight and bayestestR generics the rest of the R Bayesian ecosystem is built on, while pushing the OpenCL kernels out into a separate nmathopencl dependency that carries CRAN Windows binaries. It returned to CRAN in August after an archival over a configure policy issue.
◆ Where it's heading
The arc is about removing reasons not to use it. GPU support was previously blocked on Windows because the OpenCL kernels were vendored; splitting them into a CRAN package with binaries fixed that. The ecosystem work does the same thing for tooling — a glmb fit now responds to get_parameters, get_priors, simulate_prior and check_prior, so it drops into workflows built around easystats rather than requiring its own. The CRAN archival and the configure fixes that followed show how much of the effort goes into distribution rather than modelling.
◆ Prediction
get_priors() returning the full prior specification rather than a marginal table is the kind of detail that invites further bayestestR integration, and the diagnostic surface is the least built-out part of what has shipped so far.
lstar
5.0ANALYTICS
A single-cell data store commits to Zarr v3 and range-readable hosting across four language surfaces
◆ Current state
lstar stores single-cell data behind one C++ core with Python, R and JS/WASM bindings, and ships a browser viewer that reads the store directly. Zarr v3 is now the default on-disk format across all four surfaces, with zstd compression and sharding that packs many chunks into fewer objects. Viewer stores are compressed per field and resolved at chunk granularity, so a hosted viewer fetches only what it displays. The tag stream carries both lstar and lstar-sc releases.
◆ Where it's heading
The through-line is making a hosted store cheap to read. Sharding addresses the file-per-chunk explosion that makes many-chunk arrays awkward to host; per-field compression with chunk-granular resolution means colouring an embedding by one gene fetches one column rather than an array. The 0.2.x patches are the cost of maintaining four surfaces at once — a WASM heap crash that only browsers exercise, and a count-basis orientation defect where all three surfaces normalized in memory and none owned the on-disk layout.
◆ Prediction
The orientation bug's root cause — no surface owning the on-disk representation while all three normalized in memory — is the kind of gap that usually produces a validation or ownership change rather than another point fix.
Alternatives to glmbayes and lstar
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 glmbayes or lstar.
piecepackr
A board game graphics package runs one of the most disciplined deprecation cycles in R.
e2tree
The explainable-ensemble-tree package now measures whether its own explanations are faithful.
discretefdr
The discrete-data FDR package is being pared into one piece of a larger multiple-testing suite.
contentanalysis
A scientific-text analysis package moved from counting citations to classifying argument structure.
relialearnr
The teaching arm of an R reliability suite keeps pace with whatever its analysis siblings ship.
See all glmbayes alternatives → · See all lstar alternatives →
Recent activity from glmbayes and lstar
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10d agoglmbayesBack on CRAN after a configure policy fix
- 21d agolstarViewer count-basis orientation fixed; existing stores need re-prep
- 22d agoglmbayesOpenCL split out to nmathopencl; insight and bayestestR integration ⚡
- 26d agolstarWASM viewer crash on resizable heaps fixed
- 1mo agolstarlstar 0.2.0 ⚡
- 1mo agolstarMeasure state inferred from content, not slot name
- 1mo agoglmbayesMulti-response models and conjugate GLM priors
- 3mo agoglmbayesOpenCL kernels restructured and a binomial GPU bug fixed
- 3mo agoglmbayesVersion bump for CRAN resubmission
- 1y agoglmbayesCRAN-ready beta with the core S3 interface
Frequently asked questions
What is the difference between glmbayes and lstar?
They serve adjacent needs but don't currently overlap on shipped themes. glmbayes is currently shipping more aggressively (velocity 6.3 vs 5.0), with 1 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.
Is glmbayes better than lstar?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. glmbayes is currently shipping more aggressively (velocity 6.3 vs 5.0), with 1 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.
What are the best alternatives to glmbayes?
Top glmbayes alternatives in Analytics are ranked by recent ship velocity. Browse the "glmbayes alternatives" section above for the current picks, or visit /alternatives/glmbayes for the full list with editorial commentary on each.
What are the best alternatives to lstar?
Top lstar alternatives in Analytics are ranked by recent ship velocity. Browse the "lstar alternatives" section above for the current picks, or visit /alternatives/lstar for the full list with editorial commentary on each.