Package: fdacluster
Title: Joint Clustering and Alignment of Functional Data
Version: 0.4.2.9000
Authors@R: c(
    person(given = "Aymeric",
           family = "Stamm",
           role = c("aut", "cre"),
           email = "aymeric.stamm@cnrs.fr",
           comment = c(ORCID = "0000-0002-8725-3654")),
    person(given = "Laura",
           family = "Sangalli",
           role = "ctb",
           email = "laura.sangalli@polimi.it"),
    person(given = "Piercesare",
           family = "Secchi",
           role = "ctb",
           email = "piercesare.secchi@polimi.it"),
    person(given = "Simone",
           family = "Vantini",
           role = "ctb",
           email = "simone.vantini@polimi.it"),
    person(given = "Valeria",
           family = "Vitelli",
           role = "ctb",
           email = "valeria.vitelli@medisin.uio.no"),
    person(given = "Alessandro",
           family = "Zito",
           role = "ctb",
           email = "zito.ales@gmail.com"))
Description: Implementations of the k-means, hierarchical agglomerative
        and DBSCAN clustering methods for functional data which allows
        for jointly aligning and clustering curves. It supports
        functional data defined on one-dimensional domains but possibly
        evaluating in multivariate codomains. It supports functional
        data defined in arrays but also via the 'fd' and 'funData'
        classes for functional data defined in the 'fda' and 'funData'
        packages respectively. It currently supports shift, dilation
        and affine warping functions for functional data defined on the
        real line and uses the SRVF framework to handle
        boundary-preserving warping for functional data defined on a
        specific interval. Main reference for the k-means algorithm:
        Sangalli L.M., Secchi P., Vantini S., Vitelli V. (2010) "k-mean
        alignment for curve clustering"
        <doi:10.1016/j.csda.2009.12.008>. Main reference for the SRVF
        framework: Tucker, J. D., Wu, W., & Srivastava, A. (2013)
        "Generative models for functional data using phase and
        amplitude separation" <doi:10.1016/j.csda.2012.12.001>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
LinkingTo: Rcpp, RcppArmadillo, nloptr
RoxygenNote: 7.3.3
Roxygen: list(markdown = TRUE)
Suggests: fda, funData, future, knitr, rmarkdown, testthat (>= 3.0.0),
        withr
Imports: cli, cluster, dbscan, fdasrvf, future.apply, ggplot2, lpSolve,
        nloptr, progressr, Rcpp, rlang, tibble
Depends: R (>= 4.2.0)
URL: https://astamm.github.io/fdacluster/,
        https://github.com/astamm/fdacluster
Config/testthat/edition: 3
VignetteBuilder: knitr
Config/pak/sysreqs: cmake make libicu-dev libuv1-dev libssl-dev
Repository: https://astamm.r-universe.dev
Date/Publication: 2026-01-15 09:39:05 UTC
RemoteUrl: https://github.com/astamm/fdacluster
RemoteRef: HEAD
RemoteSha: 2c2f40e8b5b0fc9c841794a946d4a00edf8f56fb
NeedsCompilation: yes
Packaged: 2026-06-14 07:56:45 UTC; root
Author: Aymeric Stamm [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-8725-3654>),
  Laura Sangalli [ctb],
  Piercesare Secchi [ctb],
  Simone Vantini [ctb],
  Valeria Vitelli [ctb],
  Alessandro Zito [ctb]
Maintainer: Aymeric Stamm <aymeric.stamm@cnrs.fr>