person("Bruno", "Nicenboim", role = c("ctb")))

Title: Leave One Out Kernel Density Estimates for Outlier Detection
person("Rob", "Hyndman", email = "rob.hyndman@monash.edu",
Description: Outlier detection using leave-one-out kernel density estimates and
extreme value theory. The bandwidth for kernel density estimates is computed
using persistent homology, a technique in topological data analysis. Using
peak-over-threshold method, a generalized Pareto distribution is fitted to
the log of leave-one-out kde values to identify outliers.
Imports: TDAstats, evd, RANN, ggplot2, tidyr

person("Chris", "Fraley", role = "ctb", email = "fraley@u.washington.edu")

Title: Functions Similar to VLOOKUP in Excel
Description: Simple functions to lookup items in key-value pairs. See  Mehta (2021) <doi:10.1007/978-1-4842-6613-7_6>.
Packaged: 2021-04-12 18:54:06 UTC; wrightkevi

Authors@R: c(person('Enzo', 'Jia', email = 'enzo.jia@gmail.com', role = c('aut', 'cre')),
person('Marc', 'Maier', email = 'mmaier@massmutual.com', role = 'aut'))
Description: Fits look-up tables by filling entries with the mean or median values of observations
fall in partitions of the feature space. Partitions can be determined by user of the
package using input argument feature.boundaries, and dimensions of the feature space
can be any combination of continuous and categorical features provided by the data set.
A Predict function directly fetches corresponding entry value, and a default value is
defined as the mean or median of all available observations.
The table and other components are represented using the S4 class lookupTable.

Title: Interactive Statistical Data Visualization
Description: An extendable toolkit for interactive data visualization and exploration.
Imports: tools, graphics, grDevices, utils, stats
Suggests: maps, sp, graph, scagnostics, PairViz, RColorBrewer,
RnavGraphImageData, rworldmap, rgl, Rgraphviz, RDRToolbox,
kernlab, scales, MASS, dplyr, testthat, knitr, rmarkdown

kernlab, scales, MASS, testthat, knitr, rmarkdown