Allows users to explore and plot data from the
    National Oceanic and Atmospheric Administration (NOAA) 
    Storm Events database through R for United States counties. 
    Functionality includes matching storm event listings by time and 
    location to hurricane best tracks data. This work was 
    supported by grants from the Colorado Water Center, the National Institute 
    of Environmental Health Sciences (R00ES022631) and the National Science 
    Foundation (1331399).

Generate pseudonymous animal names that are delightful and easy to 
    remember like the Likable Leech and the Proud Chickadee. A unique pseudonym 
    can be created for every unique element in a vector or row in a data frame. 
    Pseudonyms can be customized and tracked over time, so that the same input 
    is always assigned the same pseudonym.

A Bayesian approach to estimate the number of occurred-but-not-yet-reported cases from incomplete, time-stamped reporting data for disease outbreaks. 'NobBS' learns the reporting delay distribution and the time evolution of the epidemic curve to produce smoothed nowcasts in both stable and time-varying case reporting settings, as described in McGough et al. (2020) <doi:10.1371/journal.pcbi.1007735>.

Designed to be compatible with the 'R' package 'DBI' (Database Interface)
    when connecting to Amazon Web Service ('AWS') Athena <https://aws.amazon.com/athena/>.
    To do this the 'R' 'AWS' Software Development Kit ('SDK') 'paws' 
    <https://github.com/paws-r/paws> is used as a driver.

Simplified JSON document database access and manipulation,
     providing a common API across supported 'NoSQL' databases 
     'Elasticsearch', 'CouchDB', 'MongoDB' as well as 
     'SQLite/JSON1', 'PostgreSQL', and 'DuckDB'.

Given any graph, the 'node2vec' algorithm can learn continuous feature representations for the nodes, which can then be used for various downstream machine learning tasks.The techniques are detailed in the paper "node2vec: Scalable Feature Learning for Networks" by Aditya Grover, Jure Leskovec(2016),available at <arXiv:1607.00653>.