A flexible tool that allows generating bespoke
    air transport statistics for urban studies based on publicly available
    data from the Bureau of Transport Statistics (BTS) in the United States
    <https://www.transtats.bts.gov/databases.asp?Z1qr_VQ=E&Z1qr_Qr5p=N8vn6v10&f7owrp6_VQF=D>.

Data reduction, visualization and statistical analysis of measurements of orientation of archaeological structures, following Silva (2020) <doi:10.1016/j.jas.2020.105138>.

'Slack' <https://slack.com/> provides a service for teams to
    collaborate by sharing messages, images, links, files and more.
    Functions are provided that make it possible to interact with the
    'Slack' platform 'API'. When you need to share information or data
    from R, rather than resort to copy/ paste in e-mails or other services
    like 'Skype' <https://www.skype.com/en/>, you can use this package to
    send well-formatted output from multiple R objects and expressions to
    all teammates at the same time with little effort. You can also send
    images from the current graphics device, R objects, and upload files.

Data structures and algorithms for sparse arrays and matrices,
  based on index arrays and simple triplet representations, respectively.

Slanted matrices and ordered clustering for better visualization of similarity data.

Alternative to using withCallingHandlers() in the simple case of catch 
  and rethrow. The `%!%` operator evaluates the expression on its left hand side, 
  and if an error occurs, the right hand side is used to construct a new error
  that embeds the original error.

A self-contained hypothesis is tested for a given pathway of longitudinal omics. 'SlaPMEG' is a two-step procedure. First, a shared latent process mixed model is fitted over the longitudinal measures of omics in a pathway. This shared model allows deviation from the shared process at subject level (a random intercept, slope, or both per subject) and also at omic level (a random effect per omic). These random effects summarize the longitudinal trend of the observations which can be used to test for group differences using 'Globaltest' in the second step. If the pathway is large or the shared effect is small, the package fits a series of pairwise models and estimates the shared random effects based on them.