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cff-version: 1.2.0
message: 'To cite package "fda.vi" in publications use:'
type: software
license: MIT
title: 'fda.vi: Functional Data Analysis using Variational Inference'
version: 1.0.0
doi: 10.32614/CRAN.package.fda.vi
abstract: 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:
- family-names: Souza
  given-names: Camila
  name-particle: de
  email: camila.souza@uwo.ca
- family-names: Kinsey
  given-names: Stephen
- family-names: Cruz
  given-names: Ana Carolina
  name-particle: da
- family-names: Toledo Oliveira Sousa
  given-names: Pedro Henrique
repository: https://desouzalab.r-universe.dev
repository-code: https://github.com/desouzalab/fda.vi
commit: 7bc5fb3cd79e72bb87d234841a3a706dd57560b1
url: https://github.com/desouzalab/fda.vi
date-released: '2026-04-14'
contact:
- family-names: Souza
  given-names: Camila
  name-particle: de
  email: camila.souza@uwo.ca