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Comparison · Analytics
affiner vs spatstat.model
A side-by-side editorial comparison of affiner and spatstat.model — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
affiner vs spatstat.model: at a glance
What is affiner?
affiner is quietly turning a grid transformation helper into a small computational geometry library.
An R package that began as a wrapper around grid's affine transformation primitives, with an angle vector class supporting degrees, radians, half-turns, turns and gradians so users need not convert by hand. Four releases in roughly eighteen months. The recent two have expanded well past that starting point into geometric objects and the predicates that operate on them.
What is spatstat.model?
spatstat's inference layer builds out determinantal and cluster process fitting
spatstat.model fits point process models and provides the diagnostics that go with them. The recent window is dominated by determinantal point process work — a variance-covariance matrix and more diagnostics in 3.7-2, additional `intensity` and `repul` methods in 3.7-1, and ROC curves for determinantal models in 3.5-0. Cluster and Cox process inference has advanced in parallel, with Waagepetersen's composite likelihood arriving in 3.6-1.
affiner vs spatstat.model: editorial side-by-side
affiner
0.0ANALYTICS
affiner is quietly turning a grid transformation helper into a small computational geometry library.
◆ Current state
An R package that began as a wrapper around grid's affine transformation primitives, with an angle vector class supporting degrees, radians, half-turns, turns and gradians so users need not convert by hand. Four releases in roughly eighteen months. The recent two have expanded well past that starting point into geometric objects and the predicates that operate on them.
◆ Where it's heading
The direction is clear from the order things arrived. Version 0.2.1 added the predicate layer first — has_intersection(), intersection(), is_equivalent() and is_parallel() as S3 generics working across angle vectors, points, lines and planes. Version 0.3.1 then supplied the objects those generics need, with Ellipse2D, Polygon2D and Segment2D R6 classes plus constructors for rectangles, regular n-gons and isotoxal star polygons, and dot products at one, two and three dimensions. Building the operations before the shapes is unusual ordering but it means each new object type arrives already composable with everything else.
◆ Prediction
Expect more 2D and 3D object types filling out the same generic interface, and the geometry side to keep outgrowing the grid-transformation wrapper the package was named for.
spatstat.model
2.5ANALYTICS
spatstat's inference layer builds out determinantal and cluster process fitting
◆ Current state
spatstat.model fits point process models and provides the diagnostics that go with them. The recent window is dominated by determinantal point process work — a variance-covariance matrix and more diagnostics in 3.7-2, additional `intensity` and `repul` methods in 3.7-1, and ROC curves for determinantal models in 3.5-0. Cluster and Cox process inference has advanced in parallel, with Waagepetersen's composite likelihood arriving in 3.6-1.
◆ Where it's heading
The pattern is that model classes enter the package as fitting machinery first and only later gain the apparatus that makes them usable in practice — standard errors, diagnostics, residuals, model checking. Determinantal processes are visibly midway through that progression, reaching variance-covariance estimation only in the most recent release. Around this, the package has been broadening where models can be fitted at all: replicated point patterns on linear networks in 3.5-0, extended spatial logistic regression, and conversion of recursively partitioned models to tessellations.
◆ Prediction
Expect determinantal model support to keep filling out along the same path other model classes took, since variance estimation has only just arrived and partial residuals already exist for the cluster and Cox families. The entries do not signal a move into three dimensions here, unlike the geometry and simulation packages.
Alternatives to affiner and spatstat.model
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 affiner or spatstat.model.
epiworldR
epiworldR is a thin R shell whose releases track the C++ simulator underneath it
watina
A groundwater database client that has started doing the domain analysis too
inbospatial
A thin R wrapper over Flemish geospatial services, adding one standard at a time
Fluent Bit
Fluent Bit keeps two lines alive while the 5.x branch quietly opens 5.1.
OpenCTI
OpenCTI is rebuilding its connector layer into a marketplace and wiring the platform to XTM Hub
See all affiner alternatives → · See all spatstat.model alternatives →
Recent activity from affiner and spatstat.model
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 18d agospatstat.modelVariance-covariance and diagnostics for determinantal models
- 2mo agospatstat.modelMore intensity and repul methods; boundary-aware predictions
- 3mo agoaffinerEllipse, polygon and segment objects, with star and n-gon constructors
- 6mo agospatstat.modelComposite likelihood for cluster processes
- 6mo agoaffinerIntersection, equivalence and parallelism generics across geometric types
- 8mo agospatstat.modelReplicated network models and partial residuals
- 10mo agospatstat.modelintensity.ppm improvements for Geyer models
- 1y agospatstat.modelROC curve support substantially extended
- 1y agoaffinerIsocube border fill forced transparent
- 1y agoaffinerInitial release: affine grob wrappers and multi-unit angle vectors
Frequently asked questions
What is the difference between affiner and spatstat.model?
Both compete on the same themes — r-package — within Analytics. spatstat.model is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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 affiner better than spatstat.model?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. spatstat.model is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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 affiner?
Top affiner alternatives in Analytics are ranked by recent ship velocity. Browse the "affiner alternatives" section above for the current picks, or visit /alternatives/affiner-r for the full list with editorial commentary on each.
What are the best alternatives to spatstat.model?
Top spatstat.model alternatives in Analytics are ranked by recent ship velocity. Browse the "spatstat.model alternatives" section above for the current picks, or visit /alternatives/spatstat-model for the full list with editorial commentary on each.