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fdadensity  

Functional Data Analysis for Density Functions by Transformation to a Hilbert Space
View on CRAN: Click here


Download and install fdadensity package within the R console
Install from CRAN:
install.packages("fdadensity")

Install from Github:
library("remotes")
install_github("cran/fdadensity")

Install by package version:
library("remotes")
install_version("fdadensity", "0.1.2")



Attach the package and use:
library("fdadensity")
Maintained by
Alexander Petersen
[Scholar Profile | Author Map]
First Published: 2017-10-16
Latest Update: 2019-12-05
Description:
An implementation of the methodology described in Petersen and Mueller (2016) for the functional data analysis of samples of density functions. Densities are first transformed to their corresponding log quantile densities, followed by ordinary Functional Principal Components Analysis (FPCA). Transformation modes of variation yield improved interpretation of the variability in the data as compared to FPCA on the densities themselves. The standard fraction of variance explained (FVE) criterion commonly used for functional data is adapted to the transformation setting, also allowing for an alternative quantification of variability for density data through the Wasserstein metric of optimal transport.
How to cite:
Alexander Petersen (2017). fdadensity: Functional Data Analysis for Density Functions by Transformation to a Hilbert Space. R package version 0.1.2, https://cran.r-project.org/web/packages/fdadensity. Accessed 10 Apr. 2025.
Previous versions and publish date:
0.1.0 (2017-10-16 20:13), 0.1.1 (2018-02-08 22:49), 0.1.2 (2019-12-05 07:20)
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Complete documentation for fdadensity
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