There are a number of binary files associated with the
    'Webdriver'/'Selenium' project. This package provides functions to download
    these binaries and to manage processes involving them.

Assortativity coefficients, centrality measures, 
    and clustering coefficients for weighted and directed networks.
    Rewiring unweighted networks with given assortativity coefficients.
    Generating general preferential attachment networks.

Functions for finding and pulling data from the
  'Wisconsin Department of Natural Resources ArcGIS REST APIs'
  <https://dnrmaps.wi.gov/arcgis/rest/services> and 
  <https://dnrmaps.wi.gov/arcgis2/rest/services>.

Fetch and clean data from the World Database on Protected
    Areas (WDPA) and the World Database on Other Effective Area-Based
    Conservation Measures (WDOECM). Data is obtained from Protected Planet
    <https://www.protectedplanet.net/en>. To augment data cleaning procedures,
    users can install the 'prepr' R package (available at
    <https://github.com/prioritizr/prepr>). For more information on this
    package, see Hanson (2022) <doi:10.21105/joss.04594>.

Numerous time series admit autoregressive moving average (ARMA)
  representations, in which the errors are uncorrelated but not necessarily
  independent.
  These models are called weak ARMA by opposition to the standard ARMA models, 
  also called strong ARMA models, in which the error terms are supposed to be 
  independent and identically distributed (iid).
  This package allows the study of nonlinear time series models through weak 
  ARMA representations.
  It determines identification, estimation and validation for ARMA models and 
  for AR and MA models in particular. 
  Functions can also be used in the strong case.
  This package also works on white noises by omitting arguments 'p', 'q', 'ar'
  and 'ma'.
  See Francq, C. and Zakoïan, J. (1998) <doi:10.1016/S0378-3758(97)00139-0> and 
  Boubacar Maïnassara, Y. and Saussereau, B. (2018)
  <doi:10.1080/01621459.2017.1380030> for more details.