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Comparison · Infra & APIs

mice vs tf

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

mice vs tf: at a glance

Featuremicetf
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesmissing-data, multiple-imputation, statistics, r-packagefunctional-data-analysis, vctrs, multivariate, r-packages
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is mice?

mice can finally predict, not just estimate, from multiply imputed data.

mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.

Read the full mice trajectory →

What is tf?

tf gave functional data a second dimension: curves whose values are vectors.

tf supplies the vector classes underneath the tidyfun stack — tfd for raw functional observations, tfb for basis-represented ones, both built on vctrs so curves sit in a data frame column and behave like any other vector. Until July that codomain was scalar. The 0.5.0 release adds tfd_mv and tfb_mv, classes for functions whose values are vectors in R^d, and rebuilds the analysis verbs to match.

Read the full tf trajectory →

mice vs tf: editorial side-by-side

M
mice
INFRA · APIS
0.0

mice can finally predict, not just estimate, from multiply imputed data.

◆ Current state

mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.

◆ Where it's heading

Two things are happening. The imputation method catalogue keeps widening — lasso variants, multivariate PMM, categorical PMM via canonical correlation — while the pooling side is being extended past its original purpose, first to synthetic data, now to predictions on held-out sets. That second thread points at predictive modelling workflows rather than the inferential ones mice was built for. Meanwhile the maintainers keep finding consequential old bugs: the augment() ordered-factor defect in 3.18.0 had been silently degrading ordinal imputations for years.

◆ Prediction

predict_mi() is framed around evaluating predictive performance on test sets, and the ignore argument added in 3.12.0 already exists to hold out rows from the imputation model. Expect the next work to join those up into a fuller train/test story for imputed data, since the pieces are now in place but not yet connected.

T
tf
INFRA · APIS
0.0

tf gave functional data a second dimension: curves whose values are vectors.

◆ Current state

tf supplies the vector classes underneath the tidyfun stack — tfd for raw functional observations, tfb for basis-represented ones, both built on vctrs so curves sit in a data frame column and behave like any other vector. Until July that codomain was scalar. The 0.5.0 release adds tfd_mv and tfb_mv, classes for functions whose values are vectors in R^d, and rebuilds the analysis verbs to match.

◆ Where it's heading

The package is widening what a functional observation can be, then porting the toolkit onto it. Registration arrived first in 0.4.0 for univariate curves and immediately gained an srvf_mv method for aligning components jointly, and tfb_mfpc() ports principal component analysis to the multivariate case with a single set of scores shared across components. Alongside that runs steady dependency shedding — mvtnorm and pracma both replaced by inlined samplers that reproduce prior draws bit-for-bit, glue dropped for cli in the previous release — and an unusually long tail of NA-handling and edge-case fixes, several caught in pre-release review of the new classes.

◆ Prediction

The new classes ship with FPCA, registration and shape alignment but the release notes describe tidyfun::tf_unnest() as the consumer of one new export, so the visible next step is the rest of the tidyfun stack catching up to vector-valued columns. Expect follow-up patches on the vctrs casting paths, which is where most of this release's late fixes clustered.

Alternatives to mice and tf

Other Infra & APIs 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 mice or tf.

See all mice alternatives → · See all tf alternatives →

Recent activity from mice and tf

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

  1. 1mo agotfVector-valued functional data becomes a first-class type
  2. 5mo agotfCurve registration, five depth measures and sub-domain splitting
  3. 8mo agomicemice 3.19.0
  4. 1y agomicemice 3.18.0
  5. 1y agomicemice 3.17.0
  6. 2y agotfFix: tf_crosscov normalization
  7. 3y agomicemice 3.16.0
  8. 3y agomicemice 3.15.0
  9. 4y agomicemice 3.14.0

Frequently asked questions

What is the difference between mice and tf?

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

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mice and tf 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 Infra & APIs products to evaluate alongside.

What are the best alternatives to mice?

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

What are the best alternatives to tf?

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