Tools for analyzing multi-dimensional point process models

Construct Polygons Summarising the Location and Variability of
Point Sets
c(person("Jonathan", "Keith", role = c("aut", "cre"),
email = "jonathan.keith@monash.edu"),
person("Ken", "Clarkson", role = "aut"),
person("Eric", "Hufschmid", role = "ctb"),
person("AT&T", role = "cph"))
Various applications in invasive species biology,
conservation biology, epidemiology and elsewhere involve
sampling of sets of 2D points from a posterior distribution.
The number of such point sets may be large, say 1000 or 10000.
This package facilitates visualisation of such output by
constructing seven nested polygons representing the location and
variability of the point sets. This can be used, for example, to
visualise the range boundary of a species, and uncertainty in
the location of that boundary.
Jonathan Keith [aut, cre],
Ken Clarkson [aut],
Eric Hufschmid [ctb],
AT&T [cph]

Helper Functions for Use with "ProjectTemplate"
c(person(given = "Rich",
family = "Leyshon",
role = c("aut", "cph", "cre"),
email = "leyshonrr@hotmail.co.uk"),
person(given = "Andrew",
family = "Simmons",
role = "ctb",
email = "akwsimmo@gmail.com"))
Utility functions produced specifically for (but not limited to)
working with 'ProjectTemplate' data pipelines. This package helps to quickly
create and manage sequentially numbered scripts, quickly set up logging with
'log4r' and functions to help debug and monitor procedures.
ProjectTemplate (>= 0.9.3), testthat, knitr, rmarkdown,
markdown, covr
Rich Leyshon [aut, cph, cre],
Andrew Simmons [ctb]

Stemming Algorithms for the Portuguese Language
Wraps a collection of stemming algorithms for the Portuguese
Language.
dplyr, hunspell, magrittr, rslp, SnowballC, stringr, tidyr

person("Daniel", "Falbel", email = "dfalbel@gmail.com",
role = c("aut", "cre"))
dplyr, hunspell, magrittr, rslp, SnowballC, stringr, tidyr,
tokenizers

dplyr, hunspell, magrittr, rslp, SnowballC, stringr, tidyr,
tokenizers, tibble

Tail Index Estimation for Power Law Distributions
c(person("Ranjiva", "Munasinghe", email = "ranjiva@mindlanka.org",
role = "aut"),
person("Pathum", "Kossinna", email = "pathum@mindlanka.org",
role = c("cre", "aut")),
person("Dovini", "Jayasinghe", email = "dovini@mindlanka.org",
role = "aut"),
person("Dilanka", "Wijeratne", email = "dilanka@mindlanka.org",
role = "aut"))
Various estimation methods for the shape parameter of Pareto
distributed data. This package contains functions for various estimation
methods such as maximum likelihood
(Newman, 2005)<doi:10.1016/j.cities.2012.03.001>,
Hill's estimator (Hill, 1975)<doi:10.1214/aos/1176343247>,
least squares (Zaher et al., 2014)<doi:10.9734/BJMCS/2014/10890>,
method of moments (Rytgaard, 1990)<doi:10.2143/AST.20.2.2005443>,
percentiles (Bhatti et al., 2018)<doi:10.1371/journal.pone.0196456>,
and weighted least squares (Nair et al., 2019) to estimate the shape
parameter of Pareto distributed data. It also provides both a heuristic
method (Hubert et al., 2013)<doi:10.1016/j.csda.2012.07.011> and a
goodness of fit test
(Gulati and Shapiro, 2008)<doi:10.1007/978-0-8176-4619-6> for testing for
Pareto data as well as a method for generating Pareto distributed data.
Ranjiva Munasinghe [aut],
Pathum Kossinna [cre, aut],
Dovini Jayasinghe [aut],
Dilanka Wijeratne [aut]