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fasster vs RMVMR

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

fasster vs RMVMR: at a glance

FeaturefassterRMVMR
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themestime series forecasting, state space models, fable, multiple seasonalitymendelian randomization, r, radial methods, genetics
Last editorial update2h ago1h ago
WebsiteVisit →Visit →

What is fasster?

fasster arrives as a fable-compatible state space model for switching seasonality.

fasster implements FASSTER, a state space model with a switching component in the measurement equation, aimed at series carrying several seasonal patterns and abrupt structural change. Version 0.2.0 is the first substantive release: a formula interface with trend(), season(), fourier(), ARMA() and xreg() plus the %S% switching and %?% conditional operators, and the full fable method set. Parameters come from a filtering-and-smoothing heuristic rather than full optimisation.

Read the full fasster trajectory →

What is RMVMR?

RMVMR is being tidied in lockstep with MVMR, the package it wraps

RMVMR provides radial multivariable Mendelian randomization — radial IVW estimation and plots layered over the MVMR package's conditional instrument-strength machinery. It has no independent release schedule: versions arrive alongside MVMR's, pin a minimum MVMR version, and fix defects in the seam between the two. Its most recent release landed the same day as new versions of MVMR and OneSampleMR.

Read the full RMVMR trajectory →

fasster vs RMVMR: editorial side-by-side

F
fasster
ANALYTICS
0.0

fasster arrives as a fable-compatible state space model for switching seasonality.

◆ Current state

fasster implements FASSTER, a state space model with a switching component in the measurement equation, aimed at series carrying several seasonal patterns and abrupt structural change. Version 0.2.0 is the first substantive release: a formula interface with trend(), season(), fourier(), ARMA() and xreg() plus the %S% switching and %?% conditional operators, and the full fable method set. Parameters come from a filtering-and-smoothing heuristic rather than full optimisation.

◆ Where it's heading

The package sat at a 2018 development version for over seven years, so the news is that it exists as a usable model at all. Implementing the whole fable contract — forecast(), refit(), stream(), interpolate(), components() — means it slots into an existing forecasting workflow instead of asking for its own. The heuristic estimator is the open question these entries leave unanswered.

◆ Prediction

The obvious next step is supplementing the heuristic parameter estimates with proper optimisation, though the two entries here give no direct signal on timing.

R
RMVMR
ANALYTICS
0.0

RMVMR is being tidied in lockstep with MVMR, the package it wraps

◆ Current state

RMVMR provides radial multivariable Mendelian randomization — radial IVW estimation and plots layered over the MVMR package's conditional instrument-strength machinery. It has no independent release schedule: versions arrive alongside MVMR's, pin a minimum MVMR version, and fix defects in the seam between the two. Its most recent release landed the same day as new versions of MVMR and OneSampleMR.

◆ Where it's heading

The work is code hygiene with results held fixed. ivw_rmvmr() now fits the radial IVW model explicitly rather than inheriting variables left over from the orientation loop, an undocumented data element carrying unused intermediate frames is gone, and plot_rmvmr() stops recomputing univariate radial analyses it already has — roughly halving the RadialMR calls with identical output. Each note is explicit that coefficients, standard errors and degrees of freedom are unchanged, which is a deliberate contrast with MVMR's own 2026 releases, where several fixes did change reported values.

◆ Prediction

Because the package pins MVMR versions rather than vendoring behaviour, the next release most likely follows MVMR's next correctness fix; nothing in the notes points to independent feature work.

Alternatives to fasster and RMVMR

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 fasster or RMVMR.

See all fasster alternatives → · See all RMVMR alternatives →

Recent activity from fasster and RMVMR

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

  1. 1mo agoRMVMRRMVMR fixes a gencov error and halves redundant radial calls
  2. 3mo agoRMVMRRMVMR 0.4.4
  3. 4mo agoRMVMRRMVMR 0.4.3
  4. 5mo agoRMVMRRMVMR now requires MVMR 0.4.3 or later
  5. 6mo agofassterFASSTER lands as a complete fable model
  6. 1y agoRMVMRRMVMR 0.4.1
  7. 7y agofassterEarly development build

Frequently asked questions

What is the difference between fasster and RMVMR?

They serve adjacent needs but don't currently overlap on shipped themes. fasster and RMVMR 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 fasster better than RMVMR?

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

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

What are the best alternatives to RMVMR?

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