Bandwidth selectors for local linear quantile regression, including cross-validation and plug-in methods. The local linear quantile regression estimate is also implemented.

An interface to the Bayesian Weighted Sums model implemented in 'RStan'.
    It estimates the summed effect of multiple, often moderately to highly correlated,
    continuous predictors. Its applications can be found in analysis of exposure mixtures.
    The model was proposed by Hamra, Maclehose, Croen, Kauffman, and
    Newschaffer (2021) <doi:10.3390/ijerph18041373>.
    This implementation includes an extension to model binary outcome.

Performs the 'Baumgartner-Weiss-Schindler' two-sample test of equal
   probability distributions, <doi:10.2307/2533862>. Also performs
   similar rank-based tests for equal probability distributions due to
   Neuhauser <doi:10.1080/10485250108832874> and
   Murakami <doi:10.1080/00949655.2010.551516>.

Tools to design best-worst scaling designs (i.e., balanced incomplete block designs) and
    to analyze data from these designs, using aggregate and individual methods such as: difference 
    scores, Louviere, Lings, Islam, Gudergan, & Flynn (2013) <doi:10.1016/j.ijresmar.2012.10.002>; 
    analytical estimation, Lipovetsky & Conklin (2014) <doi:10.1016/j.jocm.2014.02.001>; empirical 
    Bayes, Lipovetsky & Conklin (2015) <doi:10.1142/S1793536915500028>; Elo, Hollis (2018) 
    <doi:10.3758/s13428-017-0898-2>; and network-based measures.

Functions to get and download city bike data from 
    the website and API service of each city bike service in Norway. The
    package aims to reduce time spent on getting Norwegian city bike data,
    and lower barriers to start analyzing it. The data is retrieved from
    Oslo City Bike, Bergen City Bike, and Trondheim City Bike. The data is 
    made available under NLOD 2.0 <https://data.norge.no/nlod/en/2.0>.

Shows statistics about bytes contained in a file 
  as a circle graph of deviations from mean in sigma increments. 
  The function can be useful for statistically analyze the content of files 
  in a glimpse: text files are shown as a green centered crown, compressed 
  and encrypted files should be shown as equally distributed variations with 
  a very low CV (sigma/mean), and other types of files can be classified between 
  these two categories depending on their text vs binary content, which can be 
  useful to quickly determine how information is stored inside them (databases, 
  multimedia files, etc).