Convex Clustering methods, including Kmeans algorithm,
On-line Update algorithm (Hard Competitive Learning) and Neural
Gas algorithm (Soft Competitive Learning) and calculation of
several indexes for finding the number of clusters in a data
set.

c(person("Evgenia", "Dimitriadou", role = "aut"),
person("Kurt", "Hornik", role = c("ctb", "cre"), email =
"Kurt.Hornik@R-project.org"))
Convex Clustering methods, including K-means algorithm,
On-line Update algorithm (Hard Competitive Learning) and Neural
Gas algorithm (Soft Competitive Learning), and calculation of
several indexes for finding the number of clusters in a data
set.
Evgenia Dimitriadou [aut], Kurt Hornik [ctb, cre]

c(person("Evgenia", "Dimitriadou", role = "aut"),
person("Kurt", "Hornik", role = c("ctb", "cre"),
email = "Kurt.Hornik@R-project.org"))
Convex Clustering methods, including K-means algorithm,
On-line Update algorithm (Hard Competitive Learning) and Neural Gas
algorithm (Soft Competitive Learning), and calculation of several
indexes for finding the number of clusters in a data set.
Evgenia Dimitriadou [aut],
Kurt Hornik [ctb, cre]

c(person("Kirk", "Bansak", role = "aut",
email = "kbansak@ucsd.edu"),
person("Xiaohan", "Wu", role = c("aut", "cre"),
email = "xiw021@ucsd.edu"))
Functions to perform comparative causal mediation analysis to compare the mediation effects of different treatments via a common mediator. Results contain the estimates and confidence intervals for the two comparative causal mediation analysis estimands, as well as the ATE and ACME for each treatment. Functions provided in the package will automatically assess the comparative causal mediation analysis scope conditions (i.e. for each comparative causal mediation estimand, a numerator and denominator that are both estimated with the desired statistical significance and of the same sign). Results will be returned for each comparative causal mediation estimand only if scope conditions are met for it. See details in Bansak(2020)<doi:10.1017/pan.2019.31>.
Kirk Bansak [aut],
Xiaohan Wu [aut, cre]