ExtMallows, mc2d, PerMallows, Rcpp, stats

ExtMallows, mc2d, PerMallows, rankdist, Rcpp, stats

Generate Heatmaps Based on Partitioning Around Medoids (PAM)
c(person("Vidal", "Fey", email = "vidal.fey@gmail.com", role=c("aut", "cre")), person("Henri", "Sara", email = "henri.sara@gmail.com", role=c("aut")))
Data are partitioned (clustered) into k clusters "around medoids", which is
a more robust version of K-means implemented in the function pam() in the 'cluster' package.
The PAM algorithm is described in Kaufman and Rousseeuw (1990) <doi:10.1002/9780470316801>.
Please refer to the pam() function documentation for more references.
Clustered data is plotted as a split heatmap allowing visualisation of representative
"group-clusters" (medoids) in the data as separated fractions of the graph while those
"sub-clusters" are visualised as a traditional heatmap based on hierarchical clustering.
heatmapFlex, cluster, grDevices, graphics, stats
RColorBrewer, R.utils, readxl, readmoRe, utils, plyr, robustHD

Miscellaneous Functions for Passive Acoustic Analysis
c(
TS = person("Taiki", "Sakai", email = "taiki.sakai@noaa.gov", role = c("aut", "cre")),
JB = person("Jay", "Barlow", role = c("ctb")),
JO = person("Julie", "Oswald", role = c("ctb")))
A collection of miscellaneous functions for passive acoustics.
Much of the content here is adapted to R from code written by other people.
If you have any ideas of functions to add, please contact Taiki Sakai.
ggplot2, tuneR, seewave, dplyr, magrittr, RcppRoll,
PamBinaries, RSQLite, lubridate, rerddap, ncdf4, httr, purrr,
plotKML, hoardr, methods, geosphere, tcltk
Taiki Sakai [aut, cre],
Jay Barlow [ctb],
Julie Oswald [ctb]

ggplot2, tuneR, seewave, dplyr, magrittr, RcppRoll,
PamBinaries, RSQLite, lubridate, rerddap, ncdf4, httr, purrr,
plotKML, hoardr, methods, geosphere, tcltk, stringr

ggplot2, tuneR, seewave, dplyr, magrittr, RcppRoll,
PamBinaries, RSQLite, lubridate, rerddap, ncdf4, httr, purrr,
plotKML, hoardr, methods, geosphere, tcltk, stringr,
viridisLite