Functional Data Analysis using Variational Inference R package fda.vi version 1.0.0 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. The algorithm is described in da Cruz, A. C., de Souza, C. P., and Sousa, P. H. (2024). 'Fast Bayesian basis selection for functional data representation with correlated errors.' <doi:10.48550/arXiv.2405.20758>. Software Depends: R (>= 4.1) Imports: stats, graphics, fda, MASS, scales Suggests: testthat (>= 3.0.0), knitr, rmarkdown Camila de Souza <camila.souza@uwo.ca> Comprehensive R Archive Network (CRAN) Camila de Souza [cre], Stephen Kinsey [aut], Ana Carolina da Cruz [aut], Pedro Henrique Toledo Oliveira Sousa [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=fda.vi/LICENSE) 2026-06-20 application/tgz https://CRAN.R-project.org/package=fda.vi doi:10.32614/CRAN.package.fda.vi