tEDM
The temporal half of the stscl EDM pair, tracking its spatial sibling
Comparison · Analytics
bayestools vs dissmapr
A side-by-side editorial comparison of bayestools and dissmapr — release velocity, themes, recent moves, and the top alternatives to consider.
bayestools vs dissmapr: at a glance
What is bayestools?
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
BayesTools provides the shared JAGS fitting, prior and summary infrastructure that the author's meta-analysis packages build on. The 0.2.x line filled in modeling primitives — prior_mixture() and mixed-posterior objects in 0.2.18, expression-valued priors and lme4-style uncorrelated random effects in 0.2.20, then a run of small diagnostic fixes for mixture and spike-and-slab priors. Version 0.3.0 in May 2026 adds automatic standardization of continuous predictors, default priors for unspecified factor and continuous terms, and functions to transform prior and posterior samples back to the original scale.
What is dissmapr?
dissmapr spent its first releases becoming citable rather than adding methods.
dissmapr provides an R workflow for compositional dissimilarity and turnover — occurrence data through spatial gridding and environmental linkage to order-wise dissimilarity and bioregional mapping. All three releases to date are infrastructure: a first citable archive in June 2026, then a maturity release aligning the package with the B-Cubed software development guide. The ten-function pipeline described in the notes has not changed across them.
bayestools vs dissmapr: editorial side-by-side
bayestools
0.0ANALYTICS
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
◆ Current state
BayesTools provides the shared JAGS fitting, prior and summary infrastructure that the author's meta-analysis packages build on. The 0.2.x line filled in modeling primitives — prior_mixture() and mixed-posterior objects in 0.2.18, expression-valued priors and lme4-style uncorrelated random effects in 0.2.20, then a run of small diagnostic fixes for mixture and spike-and-slab priors. Version 0.3.0 in May 2026 adds automatic standardization of continuous predictors, default priors for unspecified factor and continuous terms, and functions to transform prior and posterior samples back to the original scale.
◆ Where it's heading
This package's releases are best read against what depends on them. The 0.2.x fixes track features appearing in RoBMA one version later, and 0.3.0 landed a single day before RoBMA 4.0.0 — the standardization and sample-transformation functions are the substrate that rewrite needed. The direction of the work is toward sensible defaults: default priors by predictor type, automatic standardization for sampling stability, and transformation back to interpretable scale so the convenience does not cost the user their units.
◆ Prediction
Given how tightly its releases track downstream needs, the next version is most likely driven by gaps surfacing in RoBMA 4.0.x rather than by independent feature work.
dissmapr
0.0ANALYTICS
dissmapr spent its first releases becoming citable rather than adding methods.
◆ Current state
dissmapr provides an R workflow for compositional dissimilarity and turnover — occurrence data through spatial gridding and environmental linkage to order-wise dissimilarity and bioregional mapping. All three releases to date are infrastructure: a first citable archive in June 2026, then a maturity release aligning the package with the B-Cubed software development guide. The ten-function pipeline described in the notes has not changed across them.
◆ Where it's heading
The work is compliance-shaped rather than method-shaped: explicit @importFrom in place of whole-namespace imports, library() calls removed from package code, roughly 11 MB of development caches dropped, a runnable README quick-start, and Zenodo archival with CITATION.cff and codemeta.json. dissmapr moves in lockstep with its B-Cubed sibling invasimapr — both tagged 0.1.0 within three minutes of each other and 0.2.0 on the same day — so releases here reflect project-wide standards deadlines more than package-specific work. The stated roadmap of additional ecological distance metrics has not yet landed.
◆ Prediction
With standards work now signed off and R CMD check clean, the next release is the first real chance for the roadmap items — additional ecological distance metrics — to arrive.
Alternatives to bayestools and dissmapr
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 bayestools or dissmapr.
spEDM
Spatial causal discovery in R, one exposed method per release
sccore
Shared plumbing for the Kharchenko single-cell stack, updated once a year
rdataone
The R client for DataONE ships slow, correctness-focused maintenance
tall
A Shiny text-mining GUI grows into a full NLP workbench at 1.0.0
nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
See all bayestools alternatives → · See all dissmapr alternatives →
Recent activity from bayestools and dissmapr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agodissmaprVersion bump; notes identical to 0.2.0
- 1mo agodissmaprB-Cubed standards alignment, docs overhaul and a citable DOI
- 1mo agodissmaprdissmapr v0.1.0: First citable release
- 3mo agobayestoolsAdds automatic predictor standardization and type-based default priors
- 8mo agobayestoolsBayesTools 0.2.23
- 8mo agobayestoolsBayesTools 0.2.22
- 11mo agobayestoolsBayesTools 0.2.21
- 1y agobayestoolsBayesTools 0.2.20
- 1y agobayestoolsBayesTools 0.2.19
Frequently asked questions
What is the difference between bayestools and dissmapr?
They serve adjacent needs but don't currently overlap on shipped themes. bayestools and dissmapr 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 bayestools better than dissmapr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bayestools and dissmapr 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 bayestools?
Top bayestools alternatives in Analytics are ranked by recent ship velocity. Browse the "bayestools alternatives" section above for the current picks, or visit /alternatives/bayestools for the full list with editorial commentary on each.
What are the best alternatives to dissmapr?
Top dissmapr alternatives in Analytics are ranked by recent ship velocity. Browse the "dissmapr alternatives" section above for the current picks, or visit /alternatives/dissmapr for the full list with editorial commentary on each.