JointFPM
Recurrent-event modelling settles, with mean_no() promoted to stable.
Comparison · Infra & APIs
netdiffuseR vs tf
A side-by-side editorial comparison of netdiffuseR and tf — release velocity, themes, recent moves, and the top alternatives to consider.
netdiffuseR vs tf: at a glance
What is netdiffuseR?
Network diffusion analysis returns from a seven-year gap able to track several behaviours at once
netdiffuseR analyses how behaviours spread through networks — exposure, adoption timing, thresholds, and simulation of diffusion processes. Its feed has a hole: four releases from 2024 to 2026 sit directly on top of three from 2016 and 2017, with the intervening versions absent. The current line is being maintained by a widening group of contributors and, at 1.24.0, was explicitly brought back to CRAN.
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.
netdiffuseR vs tf: editorial side-by-side
netdiffuseR
0.0INFRA · APIS
Network diffusion analysis returns from a seven-year gap able to track several behaviours at once
◆ Current state
netdiffuseR analyses how behaviours spread through networks — exposure, adoption timing, thresholds, and simulation of diffusion processes. Its feed has a hole: four releases from 2024 to 2026 sit directly on top of three from 2016 and 2017, with the intervening versions absent. The current line is being maintained by a widening group of contributors and, at 1.24.0, was explicitly brought back to CRAN.
◆ Where it's heading
The recent releases read as institutional rather than exploratory: CI fixes, CRAN-readiness passes, contributed PRs from new names, bundled teaching datasets. The one structural move is 1.23.0, named for multi-adoption, which alongside a refactor of the exposure and rdiffnet internals adds a function for splitting behaviours apart — the package handling several diffusing behaviours where its object model previously carried one.
◆ Prediction
With CRAN presence restored and a dataset for a teaching game added in the newest release, the near-term direction looks like classroom and workshop use rather than new method surface. Whether multi-adoption gets its own analysis functions, rather than a splitter, is the open question these notes do not answer.
tf
0.0INFRA · APIS
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 netdiffuseR 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 netdiffuseR or tf.
CptNonPar
Nonparametric change point detection swaps p-values for importance scores.
ggprism
A Prism-styled ggplot2 theme in maintenance, now surviving ggplot2 4.0.
TrendLSW
Wavelet trend estimation tightens the defaults it shipped with.
mmpca
Back from CRAN removal under a new maintainer, with the compiled layer rebuilt.
mice
mice can finally predict, not just estimate, from multiply imputed data.
See all netdiffuseR alternatives → · See all tf alternatives →
Recent activity from netdiffuseR and tf
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agotfVector-valued functional data becomes a first-class type ⚡
- 4mo agonetdiffuseREpidemic game dataset added ahead of a CRAN submission
- 5mo agotfCurve registration, five depth measures and sub-domain splitting
- 8mo agonetdiffuseRBack on CRAN with an adoption-timing diagnostic
- 1y agonetdiffuseRMulti-adoption: splitting several behaviours out of one network ⚡
- 1y agonetdiffuseRCRAN v1.22.6
- 2y agotfFix: tf_crosscov normalization
- 8y agonetdiffuseRigraph-standard plotting and repeated diffusion simulations
- 9y agonetdiffuseRBootstrapping, mentor matching, and Bass model fitting
Frequently asked questions
What is the difference between netdiffuseR and tf?
They serve adjacent needs but don't currently overlap on shipped themes. netdiffuseR 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 netdiffuseR better than tf?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. netdiffuseR 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 netdiffuseR?
Top netdiffuseR alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "netdiffuseR alternatives" section above for the current picks, or visit /alternatives/netdiffuser 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.