c(person("Zachariah", "Neville", email = "z.neville@stat.fsu.edu", role = c("aut", "cre")), person("Naomi", "Brownstein", email = "Naomi.Brownstein@moffitt.org", role = "aut"), person("Maya", "Ackerman", role = "aut"), person("Andreas", "Adolfsson", role = "aut"))
Zachariah Neville [aut, cre],
Naomi Brownstein [aut],
Maya Ackerman [aut],
Andreas Adolfsson [aut]

Causal Effects from Observational Studies with Clustered
Interference
c(person("Brian G.", "Barkley", email = "BarkleyBG@outlook.com",
role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1787-4735")),
person("Bradley", "Saul", role = c("ctb")))
Brian G. Barkley [aut, cre] (<https://orcid.org/0000-0003-1787-4735>),
Bradley Saul [ctb]
Estimating causal effects from observational studies assuming
clustered (or partial) interference. These inverse probability-weighted
estimators target new estimands arising from population-level treatment
policies. The estimands and estimators are introduced in Barkley et al.
(2017) <arXiv:1711.04834>.
testthat, rprojroot, knitr, rmarkdown, covr

Explore clustering interactively using R and GGobi
Visualise clustering algorithms with GGobi.  Contains both general code for visualising clustering results and specific visualisations for model-based, hierarchical and SOM clustering. See http://had.co.nz/clusterfly for more information.

See http://had.co.nz/reshape for more information.

Visualise clustering algorithms with GGobi.  Contains both
general code for visualising clustering results and specific
visualisations for model-based, hierarchical and SOM
clustering.
'clusterfly.r' 'data.r' 'ellipsoid.r' 'extract.r' 'ggplot.r'
'hclust.r' 'hulls.r' 'model-based.r' 'som-iteration.r' 'som.r'
'utils.r'

Visualise clustering algorithms with GGobi.  Contains both
general code for visualising clustering results and specific
visualisations for model-based, hierarchical and SOM clustering.

A hierarchical clustering method based on genetic algorithms
Jose A. Castellanos-Garzon <jantonio_cu@ieee.org>, Fernando
Diaz <fdiaz@infor.uva.es>
This package develops a genetic algorithm to build
hierarchical clusterings from a dataset. It additionally
provides a set of functions applied to cluster analysis.