fdadensity: Functional Data Analysis for Density Functions by Transformation to a Hilbert Space

An implementation of the methodology described in Petersen and Mueller (2016) <doi:10.1214/15-AOS1363> 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.

Getting started

Package details

AuthorA. Petersen, P. Z. Hadjipantelis and H.G. Mueller
MaintainerAlexander Petersen <petersen@pstat.ucsb.edu>
LicenseBSD_3_clause + file LICENSE
URL https://github.com/functionaldata/tDENS
Package repositoryView on CRAN
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fdadensity documentation built on Dec. 5, 2019, 9:07 a.m.