Package: fda.vi 1.0.0

Camila de Souza

fda.vi: Functional Data Analysis using Variational Inference

Implements a variational Expectation-Maximization (VEM) algorithm for smoothing one or multiple functional observations via basis function selection. The algorithm estimates all model parameters simultaneously and automatically, while accounting for within-curve correlation. The approach provides a flexible and computationally efficient framework for smoothing correlated functional data.

Authors:Camila de Souza [cre], Stephen Kinsey [aut], Ana Carolina da Cruz [aut], Pedro Henrique Toledo Oliveira Sousa [aut]

fda.vi_1.0.0.tar.gz
fda.vi_1.0.0.zip(r-4.7)fda.vi_1.0.0.zip(r-4.6)fda.vi_1.0.0.zip(r-4.5)
fda.vi_1.0.0.tgz(r-4.6-any)fda.vi_1.0.0.tgz(r-4.5-any)
fda.vi_1.0.0.tar.gz(r-4.7-any)fda.vi_1.0.0.tar.gz(r-4.6-any)
fda.vi_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
fda.vi/json (API)

# Install 'fda.vi' in R:
install.packages('fda.vi', repos = c('https://desouzalab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/desouzalab/fda.vi/issues

Datasets:

On CRAN:

Conda:

4.70 score 1 stars 34 mentions 4 exports 43 dependencies

Last updated from:7bc5fb3cd7. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK125
source / vignettesOK218
linux-release-x86_64OK147
macos-release-arm64OK149
macos-oldrel-arm64OK151
windows-develOK79
windows-releaseOK66
windows-oldrelOK83
wasm-releaseOK123

Exports:gcv_vemtune_vem_by_gcvvem_fitvem_smooth

Dependencies:ashbitopscliclustercolorspacecpp11deSolvefarverfdafdsFNNggplot2gluegtablehdrcdeisobandkernlabKernSmoothkslabelinglatticelifecyclelocfitMASSMatrixmclustmgcvmulticoolmvtnormnlmepcaPPpracmaR6rainbowRColorBrewerRcppRCurlrlangS7scalesvctrsviridisLitewithr

Introduction to fda.vi

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Jun 21 2026.

Last update: 2026-04-14
Started: 2026-04-14