simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
Comparison · Analytics
fastrg vs ibis.iSDM
A side-by-side editorial comparison of fastrg and ibis.iSDM — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
fastrg vs ibis.iSDM: at a glance
What is fastrg?
A fast random-graph sampler that spent 0.3.1 fixing what its parameters actually mean.
fastRG samples from generalized random dot product graphs — stochastic blockmodels, degree-corrected and overlapping variants, directed and undirected — in time proportional to the number of edges rather than nodes squared, which is what makes large sparse networks tractable. Since 0.3.1 the model is constructed and parameterised in one object, with sampling methods taking that object rather than re-specifying edge distribution at sample time.
What is ibis.iSDM?
A raster-to-terra migration is the only readable change in a feed of merge notes.
ibis.iSDM fits integrated species distribution models in R. Its release notes are GitHub's auto-generated pull-request lists, so most tags say only which branch was merged and by whom. The one release with a written note, 0.0.5, records the migration from raster to terra across the whole package, with an explicit warning that established code may break.
fastrg vs ibis.iSDM: editorial side-by-side
fastrg
0.0ANALYTICS
A fast random-graph sampler that spent 0.3.1 fixing what its parameters actually mean.
◆ Current state
fastRG samples from generalized random dot product graphs — stochastic blockmodels, degree-corrected and overlapping variants, directed and undirected — in time proportional to the number of edges rather than nodes squared, which is what makes large sparse networks tractable. Since 0.3.1 the model is constructed and parameterised in one object, with sampling methods taking that object rather than re-specifying edge distribution at sample time.
◆ Where it's heading
The package's development has been about semantic correctness more than speed. The 0.3.1 release moved edge-distribution arguments to the constructors and reinterpreted the mixing matrix S under Bernoulli parameterisation; 0.3.2 then flipped the meaning of X and Y in directed blockmodels so outgoing and incoming factors match the edge convention, and made block sorting conditional rather than unconditional. Both are corrections to what returned values mean, not to how fast they arrive. The 2025 release is CRAN documentation linking only.
◆ Prediction
With parameterisation settled and only a documentation release since 2023, the package reads as feature-complete for its sampling families. Nothing in the entries points to additional model types being queued.
ibis.iSDM
0.0ANALYTICS
A raster-to-terra migration is the only readable change in a feed of merge notes.
◆ Current state
ibis.iSDM fits integrated species distribution models in R. Its release notes are GitHub's auto-generated pull-request lists, so most tags say only which branch was merged and by whom. The one release with a written note, 0.0.5, records the migration from raster to terra across the whole package, with an explicit warning that established code may break.
◆ Where it's heading
Direction cannot be read from this feed with any confidence - three of the four visible tags carry nothing beyond merge titles and a full-changelog link. What is visible is a 2023 spent on dependency modernisation and dev-branch merges, ending with a 0.1.1 tag that December and nothing since.
◆ Prediction
These entries do not support a prediction; the notes would have to carry written content before a direction could be read from them.
Alternatives to fastrg and ibis.iSDM
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 fastrg or ibis.iSDM.
lavaanExtra
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
anyflights
A nycflights13 generator whose recent work is all about the data being right.
vinereg
Conditional density and log-likelihood fill out a vine copula regression package.
stringx
A drop-in string API for base R, kept alive by upstream check failures.
healthyR.data
From a bundled hospital dataset to a live CMS API client.
See all fastrg alternatives → · See all ibis.iSDM alternatives →
Recent activity from fastrg and ibis.iSDM
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1y agofastrgDocumentation cross-linking fixes for CRAN
- 2y agoibis.iSDMVersion 0.1.1
- 2y agofastrgDirected blockmodel X and Y factors swapped to match edge direction
- 3y agoibis.iSDMVersion 0.0.7
- 3y agoibis.iSDMVersion 0.0.6
- 3y agoibis.iSDMraster replaced by terra across the package ⚡
- 4y agofastrgfastRG 0.3.1 ⚡
Frequently asked questions
What is the difference between fastrg and ibis.iSDM?
Both compete on the same themes — r-package — within Analytics. fastrg and ibis.iSDM 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 fastrg better than ibis.iSDM?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fastrg and ibis.iSDM 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 fastrg?
Top fastrg alternatives in Analytics are ranked by recent ship velocity. Browse the "fastrg alternatives" section above for the current picks, or visit /alternatives/fastrg for the full list with editorial commentary on each.
What are the best alternatives to ibis.iSDM?
Top ibis.iSDM alternatives in Analytics are ranked by recent ship velocity. Browse the "ibis.iSDM alternatives" section above for the current picks, or visit /alternatives/ibis-isdm for the full list with editorial commentary on each.