n2kanalysis
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
Comparison · Analytics
ichimoku vs spmodel
A side-by-side editorial comparison of ichimoku and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
ichimoku vs spmodel: at a glance
What is ichimoku?
A cloud-chart package quietly swapping its dependencies for its maintainer's own libraries.
ichimoku implements Ichimoku Kinko Hyo cloud charts, strategy backtesting and an OANDA data interface for R. Recent releases are almost entirely plumbing: 1.5.7 drops RcppSimdJson in favor of secretbase for JSON parsing, following earlier releases that moved hashing to secretbase and raised the nanonext and mirai floors. The charting and strategy surface has been stable since the 1.5.0 line.
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.
ichimoku vs spmodel: editorial side-by-side
ichimoku
0.0ANALYTICS
A cloud-chart package quietly swapping its dependencies for its maintainer's own libraries.
◆ Current state
ichimoku implements Ichimoku Kinko Hyo cloud charts, strategy backtesting and an OANDA data interface for R. Recent releases are almost entirely plumbing: 1.5.7 drops RcppSimdJson in favor of secretbase for JSON parsing, following earlier releases that moved hashing to secretbase and raised the nanonext and mirai floors. The charting and strategy surface has been stable since the 1.5.0 line.
◆ Where it's heading
The visible arc is consolidation onto the maintainer's own package family — secretbase for hashing and now JSON, nanonext and mirai for concurrency — which steadily removes third-party and Rcpp-based dependencies from the install chain. Feature work is sporadic and narrow when it comes: a faster POSIXct formatter exported as a utility, a multi-session option for the Shiny app, and a fix for asymmetric strategies that failed to emit a final entry signal.
◆ Prediction
Expect further dependency consolidation as the sibling packages gain capabilities, with ichimoku adopting them shortly after release rather than shipping new charting features.
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 ichimoku 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 ichimoku or spmodel.
n1qn1c
A Fortran-descended optimizer got thread-safe, then found two flags that never worked.
ggstatsplot
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
collapse
collapse got a JSS paper and a 7x fmean speedup in the same release.
gtsummary
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
broadcast
broadcast is filling in NumPy-style array broadcasting for R, operator by operator.
See all ichimoku alternatives → · See all spmodel alternatives →
Recent activity from ichimoku and spmodel
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agospmodelTighter optimiser tolerance to avoid local maxima
- 2mo agoichimokuJSON parsing moves from RcppSimdJson to secretbase
- 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
- 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
- 1y agospmodelBlock kriging for areal averages and their uncertainty ⚡
- 1y agoichimokuFaster POSIXct formatting exported as a utility
- 1y agospmodelRobust semivariogram and new covariance types for areal models
- 1y agospmodelRange constraint option and redefined covariance type names
- 1y agoichimokuMultiple concurrent sessions in the OANDA Shiny app
- 1y agoichimokuAsymmetric strategies now emit their final entry signal
- 2y agoichimokusecretbase floor raised to 1.0.0
- 2y agoichimokuArchive verification reverts to SHA256
Frequently asked questions
What is the difference between ichimoku and spmodel?
They serve adjacent needs but don't currently overlap on shipped themes. ichimoku 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 ichimoku better than spmodel?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ichimoku 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 ichimoku?
Top ichimoku alternatives in Analytics are ranked by recent ship velocity. Browse the "ichimoku alternatives" section above for the current picks, or visit /alternatives/ichimoku 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.