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>.
Version: 1.0 Depends: R (≥ 2.15) Imports: Rcpp, graphics, stats, methods, utils, energy, fda.usc, parallelDist, osqp, truncnorm LinkingTo: Rcpp, RcppArmadillo Suggests: rmarkdown, knitr Published: 2022-05-05 DOI: 10.32614/CRAN.package.biosensors.usc Author: Juan C. Vidal [aut, cre], Marcos Matabuena [aut], Marta Karas [ctb] Maintainer: Juan C. Vidal <juan.vidal at usc.es> License: GPL-2 Copyright: see file COPYRIGHTS NeedsCompilation: yes Materials: README CRAN checks: biosensors.usc results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=biosensors.usc to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4