Package: biosensors.usc
Encoding: UTF-8
Type: Package
Title: Distributional Data Analysis Techniques for Biosensor Data
Version: 1.0
Date: 2022-04-11
Authors@R: c(
  person(given ="Juan C.", family ="Vidal", email = "juan.vidal@usc.es", role = c("aut", "cre"),
      comment = c(ORCID = "0000-0002-8682-6772")),
  person(given = "Marcos", family = "Matabuena", role = c("aut"),
      comment = c(ORCID = "0000-0003-3841-4447")),
  person(given = "Marta", family = "Karas", role = c("ctb"),
      comment = c(ORCID = "0000-0001-5889-3970"))
  )
Description: Unified and user-friendly framework for using new 
             distributional representations of biosensors data in different statistical modeling 
             tasks: regression models, hypothesis testing, cluster analysis, visualization, and 
             descriptive analysis. Distributional representations are a functional extension of 
             compositional time-range metrics and we have used them successfully so far in modeling 
             glucose profiles and accelerometer data. However, these functional representations can 
             be used to represent any biosensor data such as ECG or medical imaging such as fMRI.
             Matabuena M, Petersen A, Vidal JC, Gude F. "Glucodensities: A new representation of 
             glucose profiles using distributional data analysis" (2021) 
             <doi:10.1177/0962280221998064>.
Imports: Rcpp, graphics, stats, methods, utils, energy, fda.usc,
        parallelDist, osqp, truncnorm
Depends: R (>= 2.15)
LinkingTo: Rcpp, RcppArmadillo
LazyLoad: Yes
License: GPL-2
NeedsCompilation: yes
RoxygenNote: 7.1.1
Suggests: rmarkdown, knitr
VignetteBuilder: knitr
Packaged: 2022-05-03 19:11:30 UTC; martakaras
Author: Juan C. Vidal [aut, cre] (<https://orcid.org/0000-0002-8682-6772>),
  Marcos Matabuena [aut] (<https://orcid.org/0000-0003-3841-4447>),
  Marta Karas [ctb] (<https://orcid.org/0000-0001-5889-3970>)
Maintainer: Juan C. Vidal <juan.vidal@usc.es>
Repository: CRAN
Date/Publication: 2022-05-05 05:40:02 UTC
Built: R 4.4.3; x86_64-w64-mingw32; 2025-11-26 05:22:44 UTC; windows
Archs: x64
