Makes research involving EMDAT and related datasets easier. These Datasets are manually filled and have several formatting and compatibility issues. Weed aims to resolve these with its functions.

Calculates the WEGE (Weighted Endemism including Global 
    Endangerment index) index for a particular area. Additionally it also 
    calculates rasters of KBA's (Key Biodiversity Area) criteria (A1a, A1b, A1e, 
    and B1), Weighted endemism (WE), the EDGE (Evolutionarily Distinct and
    Globally Endangered) score, Evolutionary Distinctiveness (ED) and Extinction
    risk (ER). Farooq, H., Azevedo, J., Belluardo F., Nanvonamuquitxo, C.,
    Bennett, D., Moat, J., Soares, A., Faurby, S. & Antonelli, A. (2020)
    <doi:10.1101/2020.01.17.910299>.

A utility for working with women's basketball data. A scraping and aggregating interface for the WNBA Stats API <https://stats.wnba.com/> and ESPN's <https://www.espn.com> women's college basketball and WNBA statistics. It provides users with the capability to access the game play-by-plays, box scores, standings and results to analyze the data for themselves.

Provides a single function to fit data of an input data frame into one of the selected Weibull functions (w2, w3 and it's truncated versions), calculating the scale, location and shape parameters accordingly. The resulting plots and files are saved into the 'folder' parameter provided by the user. References: a) John C. Nash, Ravi Varadhan (2011). "Unifying Optimization Algorithms to Aid Software System Users: optimx for R" <doi:10.18637/jss.v043.i09>.

Conducts a goodness-of-fit test for the Weibull distribution (referred to as the weibullness test) and furnishes parameter estimations for both the two-parameter and three-parameter Weibull distributions. Notably, the threshold parameter is derived through correlation from the Weibull plot. Additionally, this package conducts goodness-of-fit assessments for the exponential, Gumbel, and inverse Weibull distributions, accompanied by parameter estimations.
  For more details, see Park (2017) <doi:10.23055/ijietap.2017.24.4.2848>, 
  Park (2018) <doi:10.1155/2018/6056975>, and Park (2023) <doi:10.3390/math11143156>. 
  This work was supported by the National Research Foundation of Korea (NRF) grants funded by 
  the Korea government (MSIT) (No. 2022R1A2C1091319, RS-2023-00242528).