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DistributionalDDA  

Distributional Data Analysis in Bayes Spaces
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("DistributionalDDA", "0.1.1")



Attach the package and use:
library("DistributionalDDA")
Maintained by
K. Gerald van den Boogaart
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-10-20
Latest Update: 2026-10-20
Description:
Statistical analysis of data sets whose observations are whole probability distributions, using Bayes space calculus. Distributions (provided as samples, histograms or density functions) are treated as elements of a Hilbert space, so that operations such as mean, variance, distance, principal component analysis and clustering carry over to densities. Reference measures defining the geometry of the space can be chosen and combined. The methodology was first published with peer review by van den Boogaart, Egozcue and Pawlowsky-Glahn (2014) <doi:10.1111/anzs.12074>.
How to cite:
K. Gerald van den Boogaart (2026). DistributionalDDA: Distributional Data Analysis in Bayes Spaces. R package version 0.1.1, https://cran.r-project.org/web/packages/DistributionalDDA. Accessed 25 Oct. 2026.
Previous versions and publish date:
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Complete documentation for DistributionalDDA
Functions, R codes and Examples using the DistributionalDDA R package
Full DistributionalDDA package functions and examples
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