Package: registr
Title: Curve Registration for Exponential Family Functional Data
Version: 2.1.0
Authors@R: c(
    person("Julia", "Wrobel", role = c("aut", "cre"), 
    email = "julia.wrobel@cuanschutz.edu",
    comment = c(ORCID = "0000-0001-6783-1421")),
    person("Alexander", "Bauer", role = "aut", email = "alexander.bauer@stat.uni-muenchen.de"),
    person("Erin", "McDonnell", role = "aut", email = "eim2117@cumc.columbia.edu"),
    person("Fabian", "Scheipl", role = "ctb", email = "fabian.scheipl@lmu.de"),
    person("Jeff", "Goldsmith", role = "aut", email = "jeff.goldsmith@columbia.edu")
    )
Description: A method for performing joint registration and functional principal
    component analysis for curves (functional data) that are generated from exponential family distributions. This 
    mainly implements the algorithms described in 'Wrobel et al. (2019)' <doi:10.1111/biom.12963> and further adapts them to potentially
    incomplete curves where (some) curves are not observed from the beginning and/or until the end of the common domain. Curve registration 
    can be used to better understand patterns in functional data by separating curves into phase and amplitude variability.
    This software handles both binary and continuous functional data, and is
    especially applicable in accelerometry and wearable technology.
Depends: R (>= 3.2)
Imports: tidyr, magrittr, dplyr, pbs, Rcpp (>= 0.11.5), parallel, MASS,
        utils, gamm4, lme4, mgcv, purrr, Matrix
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.0
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, knitr, rmarkdown, cowplot, ggplot2, pbapply,
        fastglm
SystemRequirements: GNU make
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2022-09-26 21:47:56 UTC; wrobelj
Author: Julia Wrobel [aut, cre] (<https://orcid.org/0000-0001-6783-1421>),
  Alexander Bauer [aut],
  Erin McDonnell [aut],
  Fabian Scheipl [ctb],
  Jeff Goldsmith [aut]
Maintainer: Julia Wrobel <julia.wrobel@cuanschutz.edu>
Repository: CRAN
Date/Publication: 2022-10-02 21:40:02 UTC
Built: R 4.2.3; x86_64-w64-mingw32; 2024-04-24 03:41:20 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
