c(person("Ju Yeong", "Kim",
email = "jkim2345@fredhutch.org",
role = c("aut", "cre", "cph")),
person("Sean", "Hughes",
comment = "Sean reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/261>",
role = "rev"),
person("Jason", "Taylor", role = "aut"))
testthat, covr, knitr, pryr, rmarkdown, DT
Ju Yeong Kim [aut, cre, cph],
Sean Hughes [rev] (Sean reviewed the package for ropensci, see
<https://github.com/ropensci/software-review/issues/261>),
Jason Taylor [aut]

c(person("Ju Yeong", "Kim",
email = "jkim2345@fredhutch.org",
role = c("aut", "cre", "cph")),
person("Sean", "Hughes",
comment = "Sean reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/261>",
role = "rev"),
person("Jason", "Taylor", role = "aut"),
person("Helen", "Miller", role = "aut"))
Ju Yeong Kim [aut, cre, cph],
Sean Hughes [rev] (Sean reviewed the package for ropensci, see
<https://github.com/ropensci/software-review/issues/261>),
Jason Taylor [aut],
Helen Miller [aut]

c(person("Ju Yeong", "Kim", role = "aut"),
person("Sean", "Hughes", role = "rev"),
person("Jason", "Taylor", email = "jmtaylor@fredhutch.org", role = c("aut", "cre")),
person("Helen", "Miller", role = "aut"),
person("CAVD DataSpace", email = "dataspace.support@scharp.org", role = "cph"))
Ju Yeong Kim [aut],
Sean Hughes [rev],
Jason Taylor [aut, cre],
Helen Miller [aut],
CAVD DataSpace [cph]

c(person("Michael", "Thrun", email= "m.thrun@gmx.net",role=c("aut","cre","cph")),person("Felix", "Pape",role=c("aut","rev")),person("Onno", "Hansen-Goos",role=c("ctr","ctb")),person("Fredericke", "Matz",role=c("ctr","ctb")),person("Alfred", "Ultsch",role=c("dtc","ctb")))
Various visualizations of high-dimensional data such as heat map and silhouette plot for grouped data, visualizations of the distribution of distances, the scatter-density plot for two variables, the Shepard density plot and many more are presented here. Additionally, 'DataVisualizations' makes it possible to inspect the distribution of each feature of a dataset visually through the combination of four methods. More detailed explanations can be found in the book of Thrun, M.C.:"Projection-Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9>.
Rcpp (>= 0.12.12), AdaptGauss, ggplot2, magrittr
Michael Thrun [aut, cre, cph],
Felix Pape [aut, rev],
Onno Hansen-Goos [ctr, ctb],
Fredericke Matz [ctr, ctb],
Alfred Ultsch [dtc, ctb]