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ichimoku vs MVMR

A side-by-side editorial comparison of ichimoku and MVMR — release velocity, themes, recent moves, and the top alternatives to consider.

ichimoku vs MVMR: at a glance

FeatureichimokuMVMR
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesfinancial-charting, technical-analysis, dependency-reduction, oandamendelian randomization, r, causal inference, genetics
Last editorial update48m ago1h ago
WebsiteVisit →Visit →

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.

Read the full ichimoku trajectory →

What is MVMR?

MVMR spent 2026 discovering its own estimators had been returning the wrong numbers

MVMR implements multivariable Mendelian randomization — conditional instrument strength, pleiotropy tests and heterogeneity-robust effect estimation from GWAS summary data. The package has been releasing steadily through 2026, and the substantive releases are all corrections rather than features. Two core routines were found to be computing the wrong quantity outright: qhet_mvmr() built weights from the minimised objective value instead of the minimiser, and strhet_mvmr() never minimised the Q-statistic at all.

Read the full MVMR trajectory →

ichimoku vs MVMR: editorial side-by-side

I
ichimoku
ANALYTICS
0.0

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.

M
MVMR
ANALYTICS
0.0

MVMR spent 2026 discovering its own estimators had been returning the wrong numbers

◆ Current state

MVMR implements multivariable Mendelian randomization — conditional instrument strength, pleiotropy tests and heterogeneity-robust effect estimation from GWAS summary data. The package has been releasing steadily through 2026, and the substantive releases are all corrections rather than features. Two core routines were found to be computing the wrong quantity outright: qhet_mvmr() built weights from the minimised objective value instead of the minimiser, and strhet_mvmr() never minimised the Q-statistic at all.

◆ Where it's heading

This is a sustained audit, not a maintenance drift. Each release since February has fixed a specific analytical defect — omitted intercepts in the exposure-on-genotype regressions, a division by zero when a gencov list held exactly two variants, covariance matrices computed wrongly for matrix inputs, a spurious covariance warning — and several explicitly warn that reported values will differ from previous versions. The strhet_mvmr() rewrite to iteratively reweighted least squares also removes a combinatorial grid that could exhaust memory past three exposures, so the function is now usable as well as correct.

◆ Prediction

The corrections have been walking through the package function by function, and the ones with published fixes so far are the heterogeneity and covariance routines; the remaining untouched estimators are the natural next stop if the audit continues at this pace.

Alternatives to ichimoku and MVMR

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 MVMR.

See all ichimoku alternatives → · See all MVMR alternatives →

Recent activity from ichimoku and MVMR

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agoMVMRMVMR rewrites strhet_mvmr() after finding it never minimised Q
  2. 1mo agoMVMRMVMR corrects qhet_mvmr() weights and three covariance bugs
  3. 2mo agoichimokuJSON parsing moves from RcppSimdJson to secretbase
  4. 3mo agoMVMRNew vignette on estimating phenotypic correlations
  5. 3mo agoMVMRMVMR 0.4.5
  6. 4mo agoMVMRMVMR 0.4.4
  7. 5mo agoMVMRMVMR restores intercepts omitted from snpcov_mvmr() regressions
  8. 1y agoichimokuFaster POSIXct formatting exported as a utility
  9. 1y agoichimokuMultiple concurrent sessions in the OANDA Shiny app
  10. 1y agoichimokuAsymmetric strategies now emit their final entry signal
  11. 2y agoichimokusecretbase floor raised to 1.0.0
  12. 2y agoichimokuArchive verification reverts to SHA256

Frequently asked questions

What is the difference between ichimoku and MVMR?

They serve adjacent needs but don't currently overlap on shipped themes. ichimoku and MVMR 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 MVMR?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ichimoku and MVMR 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 MVMR?

Top MVMR alternatives in Analytics are ranked by recent ship velocity. Browse the "MVMR alternatives" section above for the current picks, or visit /alternatives/mvmr for the full list with editorial commentary on each.