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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 |
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 |
Reference manual: | biosensors.usc.pdf |
Vignettes: |
intro_to_package |
Package source: | biosensors.usc_1.0.tar.gz |
Windows binaries: | r-devel: biosensors.usc_1.0.zip, r-release: biosensors.usc_1.0.zip, r-oldrel: biosensors.usc_1.0.zip |
macOS binaries: | r-release (arm64): biosensors.usc_1.0.tgz, r-oldrel (arm64): biosensors.usc_1.0.tgz, r-release (x86_64): biosensors.usc_1.0.tgz, r-oldrel (x86_64): biosensors.usc_1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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