S4 classes and methods for the analysis of data described by discrete distributions with finite support (e.g. frequency distributions of ratings, scores or counts observed on groups of individuals), using the L2 Wasserstein metric between quantile functions: exact distances, barycenters, variance, covariance and correlation, clustering, quantile-based PCA and MFA, two-component linear regression and reliability indices.
DDAWASS: Discrete Distribution Data Analysis with Wasserstein Distance
Irpino Antonio
2026
Abstract
S4 classes and methods for the analysis of data described by discrete distributions with finite support (e.g. frequency distributions of ratings, scores or counts observed on groups of individuals), using the L2 Wasserstein metric between quantile functions: exact distances, barycenters, variance, covariance and correlation, clustering, quantile-based PCA and MFA, two-component linear regression and reliability indices.File in questo prodotto:
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