fasterize, methods, plotwidgets, raster, rgdal, sf, Rcpp,
comat
dplyr, pbapply, testthat (>= 2.1.0), knitr, rmarkdown,
RColorBrewer, covr

Implements a computational framework for a pattern-based,
zoneless analysis, and visualization of (ethno)racial topography
(Dmowska, Stepinski, and Nowosad (2020) <doi:10.1016/j.apgeog.2020.102239>).
It is a reimagined
approach for analyzing residential segregation and racial diversity based on
the concept of 'landscape’ used in the domain of landscape ecology.

Rapid A/Ci Response (RACiR) Data Analysis
person("Joseph", "Stinziano", email = "josephstinziano@gmail.com",
role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7628-4201"))
Contains functions useful for reading in Licor 6800 files,
correcting and analyzing rapid A/Ci response (RACiR) data. Requires some
user interaction to adjust the calibration (empty chamber) data file to
a useable range. Calibration uses a 1st to 5th order polynomial as
suggested in Stinziano et al. (2017) <doi:10.1111/pce.12911>.
Data can be processed individually or batch processed for all files paired
with a given calibration file. RACiR is a trademark of LI-COR Biosciences,
and used with permission.
Joseph Stinziano [aut, cre] (<https://orcid.org/0000-0002-7628-4201>)

Loading Data from 'ActiveCampaign API v3'
Interface for loading data from 'ActiveCampaign API v3'
<https://developers.activecampaign.com/reference>. Provide functions
for getting data by deals, contacts, accounts, campaigns and messages.
dplyr, httr, pbapply, stringr, tidyr, cli

dplyr, httr, pbapply, stringr, tidyr, cli, retry

c(person(given = "Jose'", family = "Gama", role = c("aut","cre"),email = "rxprtgama@gmail.com"),
person(given = "Nick", family = "Guy", role = c("aut")))
Fundamental formulas for Radar, for attenuation, range, velocity,
effectiveness, power, scatter, doppler, geometry, radar equations, etc.
Based on Nick Guy's Python package PyRadarMet

person("Caio", "Hamamura", email = "caiohamamura@gmail.com", role = c("aut", "cre"))
A wrapper around fmsb::radarchart()
creating the radar-boxplot, a plot that was created by the
author during his doctoring in forest resources.
The radar-boxplot is a visualization feature suited for
multivariate classification/clustering. It provides an intuitive
deep understanding of the data.