JointFPM
Recurrent-event modelling settles, with mean_no() promoted to stable.
A side-by-side editorial comparison of nzilbb.vowels and tf — release velocity, themes, recent moves, and the top alternatives to consider.
A vowel-analysis package trimming dependencies after an email address got it archived.
nzilbb.vowels supports sociophonetic vowel analysis — principal component analysis over vowel measurements, Procrustes comparison of loadings, and the plotting that goes with them. Three releases are visible, all in the 0.4.x line and all small. The substantive thread is dependency removal: vegan and gghalves have both been dropped in favour of code the package controls.
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.
nzilbb.vowels supports sociophonetic vowel analysis — principal component analysis over vowel measurements, Procrustes comparison of loadings, and the plotting that goes with them. Three releases are visible, all in the 0.4.x line and all small. The substantive thread is dependency removal: vegan and gghalves have both been dropped in favour of code the package controls.
The package is reducing what it relies on, and paying for it in small interface breaks — plot_correlation_counts() lost its half_violin argument and gained a points argument in the same move. The 0.4.2 notes also record that version 0.4.1 was archived by CRAN because the maintainer's email had become unreliable, prompting a switch to an institutional address. That is administrative rather than technical, but it explains why three closely spaced patches exist at all.
With the two external plotting and ordination dependencies gone and the maintainer address stabilised, the visible pressure that produced these releases is resolved. Nothing in the entries indicates what comes next, and the history is too short to read a feature direction from.
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.
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.
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.
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 nzilbb.vowels or tf.
Recurrent-event modelling settles, with mean_no() promoted to stable.
Nonparametric change point detection swaps p-values for importance scores.
A Prism-styled ggplot2 theme in maintenance, now surviving ggplot2 4.0.
Wavelet trend estimation tightens the defaults it shipped with.
Back from CRAN removal under a new maintainer, with the compiled layer rebuilt.
mice can finally predict, not just estimate, from multiply imputed data.
See all nzilbb.vowels alternatives → · See all tf alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — dependency-reduction — within Infra & APIs. nzilbb.vowels 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nzilbb.vowels 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.
Top nzilbb.vowels alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "nzilbb.vowels alternatives" section above for the current picks, or visit /alternatives/nzilbb-vowels for the full list with editorial commentary on each.
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.