Provides access to biographical and political data about Australian 
    federal politicians who served between 1901 and 2021. This enhances how 
    reproducible research is that uses this data.

Performs approximate unconditional and permutation testing for
    2x2 contingency tables. Motivated by testing for disease association with rare
    genetic variants in case-control studies. When variants are extremely rare,
    these tests give better control of Type I error than standard tests.

Uses Auth0 API (see <https://auth0.com> for more 
    information) to use a simple authentication system. It provides 
    tools to log in and out a shiny application using social networks or a list
    of e-mails.

Manage author metadata and generate manuscript front matter.
    It produces title pages, acknowledgements, conflicts of interest, and
    contribution sections for large author lists, with helpers for validating
    and reading common spreadsheet formats.

Utilities to parse authors fields from DESCRIPTION files and
    general purpose functions to deduplicate names in database, beyond the
    specific case of R package authors.

PCA done by eigenvalue decomposition of a data correlation matrix, here it automatically determines the number of factors by eigenvalue greater than 1 and it gives the uncorrelated variables based on the rotated component scores, Such that in each principal component variable which has the high variance are selected. It will be useful for non-statisticians in selection of variables. For more information, see the <http://www.ijcem.org/papers032013/ijcem_032013_06.pdf> web page.

Calculations of the most common metrics of automated advertisement and plotting of them with trend and forecast. Calculations and description of metrics is taken from different RTB platforms support documentation. Plotting and forecasting is based on packages 'forecast', described in Rob J Hyndman and George Athanasopoulos (2021) "Forecasting: Principles and Practice" <https://otexts.com/fpp3/> and Rob J Hyndman et al "Documentation for 'forecast'" (2003) <https://pkg.robjhyndman.com/forecast/>, and 'ggplot2', described in Hadley Wickham et al "Documentation for 'ggplot2'" (2015) <https://ggplot2.tidyverse.org/>, and Hadley Wickham, Danielle Navarro, and Thomas Lin Pedersen (2015) "ggplot2: Elegant Graphics for Data Analysis" <https://ggplot2-book.org/>.