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glmbayes vs regfusionr

A side-by-side editorial comparison of glmbayes and regfusionr — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

glmbayes vs regfusionr: at a glance

Featureglmbayesregfusionr
SectorAnalyticsAnalytics
Velocity score6.33.8
Sparks · 30d11
Top themesbayesian-statistics, generalized-linear-models, opencl, r-packageneuroimaging, coordinate-mapping, freesurfer, r-package
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

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.

Read the full glmbayes trajectory →

What is regfusionr?

Registration fusion mapping goes bidirectional, and a vertex-indexing bug that silently returned wrong coordinates is fixed

regfusionr maps coordinates between volumetric brain templates (MNI152, Colin27) and the fsaverage surface. After four dormant years it returned in July 2026 with a release that fixes a coordinate-indexing bug, unblocks a previously disabled function, and completes the template-by-method matrix so all four combinations answer point queries. It also breaks compatibility by switching to the standard FREESURFER_HOME environment variable.

Read the full regfusionr trajectory →

glmbayes vs regfusionr: editorial side-by-side

G
glmbayes
ANALYTICS
6.3

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.

R
regfusionr
ANALYTICS
3.8

Registration fusion mapping goes bidirectional, and a vertex-indexing bug that silently returned wrong coordinates is fixed

◆ Current state

regfusionr maps coordinates between volumetric brain templates (MNI152, Colin27) and the fsaverage surface. After four dormant years it returned in July 2026 with a release that fixes a coordinate-indexing bug, unblocks a previously disabled function, and completes the template-by-method matrix so all four combinations answer point queries. It also breaks compatibility by switching to the standard FREESURFER_HOME environment variable.

◆ Where it's heading

The package moved from a partial implementation to a complete one in a single release. Before this, vol_coords_to_fsaverage returned coordinates indexed by query position rather than by vertex index — results that looked plausible and were wrong — and fsaverage_to_vol was guarded behind a stop(). Both are now resolved, and the new Colin27 and MNI152 convenience functions make the mapping bidirectional. The sibling package haze shipped a maintenance release 56 minutes later, marking this as a coordinated sweep across the maintainer's neuroimaging stack.

◆ Prediction

With the four template-by-method combinations closed and the coordinate bug fixed, the next release is more likely to be CRAN-adjacent packaging or documentation than new mapping capability.

Alternatives to glmbayes and regfusionr

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 regfusionr.

See all glmbayes alternatives → · See all regfusionr alternatives →

Recent activity from glmbayes and regfusionr

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 10d agoglmbayesBack on CRAN after a configure policy fix
  2. 18d agoregfusionrVersion 0.3.0 -- vol_to_fsaverage, many convenience functions and fixes
  3. 22d agoglmbayesOpenCL split out to nmathopencl; insight and bayestestR integration
  4. 1mo agoglmbayesMulti-response models and conjugate GLM priors
  5. 3mo agoglmbayesOpenCL kernels restructured and a binomial GPU bug fixed
  6. 3mo agoglmbayesVersion bump for CRAN resubmission
  7. 1y agoglmbayesCRAN-ready beta with the core S3 interface
  8. 4y agoregfusionrv0.2.0 -- surface to volume data projection
  9. 4y agoregfusionrv0.1.0: Initial release

Frequently asked questions

What is the difference between glmbayes and regfusionr?

Both compete on the same themes — r-package — within Analytics. glmbayes is currently shipping more aggressively (velocity 6.3 vs 3.8), with 1 editorial sparks in the last 30 days against 1. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is glmbayes better than regfusionr?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. glmbayes is currently shipping more aggressively (velocity 6.3 vs 3.8), with 1 editorial sparks in the last 30 days against 1. 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 regfusionr?

Top regfusionr alternatives in Analytics are ranked by recent ship velocity. Browse the "regfusionr alternatives" section above for the current picks, or visit /alternatives/regfusionr for the full list with editorial commentary on each.