Wait for a single key press at the 'R' prompt.
    This works in terminals, but does not currently work
    in the 'Windows' 'GUI', the 'OS X' 'GUI' ('R.app'),
    in 'Emacs' 'ESS', in an 'Emacs' shell buffer or in
    'R Studio'. In these cases 'keypress' stops with an
    error message.

Platform independent 'API' to access the operating system's
    credential store. Currently supports: 'Keychain' on 'macOS',
    Credential Store on 'Windows', the Secret Service 'API' on 'Linux',
    and simple, platform independent stores implemented with environment
    variables or encrypted files.  Additional storage back-ends can be
    added easily.

Decrypts passwords stored in the Gnome Keyring, macOS Keychain and
    strings encrypted with the Windows Data Protection API.

Assign and listen to keyboard shortcuts in 'shiny' using the 
  'Mousetrap' Javascript library.

Convert keys and other values to memorable phrases. 
  Includes some methods to build lists of words.

Provides functions to identify plausible and replicable factor
  structures for a set of variables via k-fold cross validation. The process
  combines the exploratory and confirmatory factor analytic approach to scale
  development (Flora & Flake, 2017) <doi:10.1037/cbs0000069> with a cross validation
  technique that maximizes the available data (Hastie, Tibshirani, & Friedman, 2009)
  <isbn:978-0-387-21606-5>. Also available are functions to determine k by drawing 
  on power analytic techniques for covariance structures (MacCallum, Browne, &
  Sugawara, 1996) <doi:10.1037/1082-989X.1.2.130>, generate model syntax, and
  summarize results in a report.

State space modelling is an efficient and flexible framework for 
    statistical inference of a broad class of time series and other data. KFAS 
    includes computationally efficient functions for Kalman filtering, smoothing, 
    forecasting, and simulation of multivariate exponential family state space models, 
    with observations from Gaussian, Poisson, binomial, negative binomial, and gamma 
    distributions. See the paper by Helske (2017) <doi:10.18637/jss.v078.i10> for details.