IDSL.MXP (>= 1.4), xml2, RNetCDF, base64enc, IDSL.IPA (>=
2.1), IDSL.UFA (>= 1.5), stats, readxl, parallel, doParallel,
foreach, RcppAlgos

IDSL.IPA (>= 2.1), IDSL.UFA (>= 1.5), doParallel, foreach,
readxl, RcppAlgos

Estimate Global Clustering in Infectious Disease
Justin Lessler <justin@jhu.edu>, Henrik Salje <hsalje@jhsph.edu>
Implements various novel and standard
clustering statistics and other analyses useful for understanding the
spread of infectious disease.

John Giles <giles@jhu.edu>, Henrik Salje <hsalje@jhsph.edu>, Justin Lessler <justin@jhu.edu>
doParallel, foreach, parallel, R (>= 2.10)

c(person("John", "Giles", role=c("aut", "ctb"), email="jrgiles@uw.edu"),
person("Henrik", "Salje", role=c("aut", "ctb"), email="hs743@cam.ac.uk"),
person("Justin", "Lessler", role=c("aut", "cre"), email="jlessler@unc.edu"))
John Giles [aut, ctb],
Henrik Salje [aut, ctb],
Justin Lessler [aut, cre]

Justin Lessler <justin@jhu.edu>, Henrik Salje <hsalje@jhsph.edu>, John Giles <gilesjohnr@gmail.com>

Identify Turtles by their Plastral Biometries
It is a method to identify individually turtles using the plastral biometries. It is also useful to detect errors on the identification of turtles as is explained in Valdeon & Longares 2015.

Isolate-Detect Methodology for Multiple Change-Point Detection
c(person("Andreas", "Anastasiou", email = "a.anastasiou@lse.ac.uk", role = c("aut", "cre")),
person("Piotr", "Fryzlewicz", email = "p.fryzlewicz@lse.ac.uk", role = "aut"))
Provides efficient implementation of the Isolate-Detect
methodology for the consistent estimation of the number and location of multiple
change-points in one-dimensional data sequences from the "deterministic
+ noise" model. For details on the Isolate-Detect methodology, please see Anastasiou and
Fryzlewicz (2018) <https://docs.wixstatic.com/ugd/24cdcc_6a0866c574654163b8255e272bc0001b.pdf>.
Currently implemented scenarios are: piecewise-constant signal with Gaussian
noise, piecewise-constant signal with heavy-tailed noise, continuous piecewise-linear
signal with Gaussian noise, continuous piecewise-linear signal with heavy-tailed noise.
Andreas Anastasiou [aut, cre],
Piotr Fryzlewicz [aut]