Similarity and Distance Quantification Between Probability
Functions
c(person("Hajk-Georg", "Drost",
                role = c("aut", "cre"),
                email = "hajk-georg.drost@tuebingen.mpg.de",
                comment = c(ORCID = "http://orcid.org/0000-0002-1567-306X")),
                person("Jakub", "Nowosad", role = c("ctb"), email="nowosad.jakub@gmail.com", comment = c(ORCID = "0000-0002-1057-3721"))
                )
Computes 46 optimized distance and similarity measures for comparing probability functions (Drost (2018) <doi:10.21105/joss.00765>). These comparisons between probability functions have their foundations in a broad range of scientific disciplines from mathematics to ecology. The aim of this package is to provide a core framework for clustering, classification, statistical inference, goodness-of-fit, non-parametric statistics, information theory, and machine learning tasks that are based on comparing univariate or multivariate probability functions.
Hajk-Georg Drost [aut, cre] (<https://orcid.org/0000-0002-1567-306X>),
  Jakub Nowosad [ctb] (<https://orcid.org/0000-0002-1057-3721>)