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biosensors.usc
View on CRAN: Click
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Download and install biosensors.usc package within the R console
Install from CRAN:
install.packages("biosensors.usc")
Install from Github:
library("remotes")
install_github("cran/biosensors.usc")
Install by package version:
library("remotes")
install_version("biosensors.usc", "1.0")
Attach the package and use:
library("biosensors.usc")
Maintained by
Juan C. Vidal
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-05-05
Latest Update: 2022-05-05
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)
.
How to cite:
Juan C. Vidal (2022). biosensors.usc: Distributional Data Analysis Techniques for Biosensor Data. R package version 1.0, https://cran.r-project.org/web/packages/biosensors.usc
Previous versions and publish date:
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Other R packages that biosensors.usc depends,
imports, suggests or enhances
Functions, R codes and Examples using
the biosensors.usc R package
Some associated functions: biosensors.usc . clustering . clustering_prediction . generate_data . hypothesis_testing . load_data . nadayara_prediction . nadayara_regression . regmod_prediction . regmod_regression . ridge_regression .
Some associated R codes: RcppExports.R . biosensors.usc.R . clustering.R . hypothesis_testing.R . load.R . nadayara.R . regmod.R . ridge.R . Full biosensors.usc package functions and examples
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