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Comparison · Analytics
arulesViz vs spmodel
A side-by-side editorial comparison of arulesViz and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
arulesViz vs spmodel: at a glance
What is arulesViz?
arulesViz finished its move to ggplot2 and has been coasting on maintenance since.
arulesViz draws the association rules produced by arules — scatterplots, matrix and grouped-matrix views, rule graphs, and a Shiny explorer. The rendering foundation has been settled since 1.5.0 made ggplot2 the default engine for most plots. The two most recent releases contain no new capability: roxygen migration and deprecation catch-up in 1.5.3, and a partial-argument-match cleanup in 1.5.4 that landed the same week as the identical fix in sibling package seriation.
What is spmodel?
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
arulesViz vs spmodel: editorial side-by-side
arulesViz
0.0ANALYTICS
arulesViz finished its move to ggplot2 and has been coasting on maintenance since.
◆ Current state
arulesViz draws the association rules produced by arules — scatterplots, matrix and grouped-matrix views, rule graphs, and a Shiny explorer. The rendering foundation has been settled since 1.5.0 made ggplot2 the default engine for most plots. The two most recent releases contain no new capability: roxygen migration and deprecation catch-up in 1.5.3, and a partial-argument-match cleanup in 1.5.4 that landed the same week as the identical fix in sibling package seriation.
◆ Where it's heading
The 2021 releases were a deliberate consolidation. 1.4-0 added ggplot2 engines and cut plotly_arules and the experimental iplots support out of the interface; 1.5.0 promoted ggplot2 to default and exposed the conversions to igraph and matrix so users could build their own views; 1.5-1 filled gaps in the graph and grouped-matrix methods. Since then the package tracks its dependencies rather than extending itself, which is a reasonable end state for a mature visualization layer.
◆ Prediction
Expect continued reactive releases keyed to ggplot2 and igraph deprecations, which have driven two of the last three updates. Nothing in these entries suggests new plot methods are planned.
spmodel
0.0ANALYTICS
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
◆ Current state
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
◆ Where it's heading
Two threads run in parallel. The first is expanding what can be predicted — point predictions, then areal averages over a region via block kriging, then better accuracy and efficiency for that path as the block size default moved from 1000 to 4000 in 0.12.0. The second is numerical trustworthiness, and it is unusually prominent here: a range-constraint option for stability in 0.9.0, a corrected log determinant of the fixed effects in the restricted log likelihood in 0.11.0, a cloud semivariogram that had been doubling the semivariance fixed in 0.11.1, and now a tighter optimiser tolerance. Several of these silently changed results before they were caught.
◆ Prediction
Expect the maintainers to keep publishing explicit reproduction instructions alongside numerical default changes, as 0.13.0 does by documenting the `control = list(reltol = 1e-4)` escape hatch. The entries give no signal of expansion beyond the current model families.
Alternatives to arulesViz and spmodel
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 arulesViz or spmodel.
geodist
geodist stays dependency-free and fast, and warns you when 'cheap' distances stop being honest.
errors
errors keeps making uncertainty print the way each scientific field expects.
CMAQ
CMAQ went global in v5.5, and has been patching that surface ever since.
enpls
enpls has not changed its statistics since 2016 — only its website, twice.
grex
grex is a lookup table with a version number — it ships when the annotation moves.
See all arulesViz alternatives → · See all spmodel alternatives →
Recent activity from arulesViz and spmodel
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agospmodelTighter optimiser tolerance to avoid local maxima
- 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
- 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
- 11mo agoarulesVizarulesViz 1.5.4: partial argument matches, translucent NA color
- 1y agospmodelBlock kriging for areal averages and their uncertainty ⚡
- 1y agospmodelRobust semivariogram and new covariance types for areal models
- 1y agospmodelRange constraint option and redefined covariance type names
- 2y agoarulesVizarulesViz 1.5.3 moves docs to roxygen, updates deprecated calls
- 4y agoarulesVizarulesViz 1.5-1 extends graph and grouped-matrix plots
- 5y agoarulesVizarulesViz 1.5.0 makes ggplot2 the default plotting engine
- 5y agoarulesVizarulesViz 1.4-0 adds ggplot2 engines, drops plotly_arules and iplots
- 7y agoarulesVizarulesViz 1.3-3 cleans up the ruleExplorer interface
Frequently asked questions
What is the difference between arulesViz and spmodel?
Both compete on the same themes — r-package — within Analytics. arulesViz and spmodel 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 arulesViz better than spmodel?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. arulesViz and spmodel 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 arulesViz?
Top arulesViz alternatives in Analytics are ranked by recent ship velocity. Browse the "arulesViz alternatives" section above for the current picks, or visit /alternatives/arulesviz-r for the full list with editorial commentary on each.
What are the best alternatives to spmodel?
Top spmodel alternatives in Analytics are ranked by recent ship velocity. Browse the "spmodel alternatives" section above for the current picks, or visit /alternatives/spmodel for the full list with editorial commentary on each.