Provides functions for Bayesian A/B testing including prior elicitation
    options based on Kass and Vaidyanathan (1992) <doi:10.1111/j.2517-6161.1992.tb01868.x>. 
    Gronau, Raj K. N., & Wagenmakers (2021) <doi:10.18637/jss.v100.i17>.

Fit and predict with the high-dimensional principal fitted
        components model.  This model is described by Cook, Forzani, and Rothman (2012)
	<doi:10.1214/11-AOS962>.

Infers directional conservative causal core (gene) networks. It is an advanced version of the algorithm C3NET by providing directional network. Gokmen Altay (2018) <doi:10.1101/271031>, bioRxiv.

Offers an interactive function for the detection of breakpoints in series.

Functionality to allow users to easily colour plots with the colour
    palettes of various academic institutions.

Package to query the Twitter Academic Research Product Track,
    providing access to full-archive search and other v2 API endpoints. Functions
    are written with academic research in mind. They provide flexibility in how 
    the user wishes to store collected data, and encourage regular storage of data
    to mitigate loss when collecting large volumes of tweets. They also provide
    workarounds to manage and reshape the format in which data is provided on
    the client side.

Processes accelerometer data from uni-axial and tri-axial devices,
    and generates data summaries. Also includes functions to plot, analyze, and
    simulate accelerometer data.

It performs Canonical Correlation Analysis and provides inferential guaranties on the correlation components. The p-values are computed following the resampling method developed in Winkler, A. M., Renaud, O., Smith, S. M., & Nichols, T. E. (2020). Permutation inference for canonical correlation analysis. NeuroImage, <doi:10.1016/j.neuroimage.2020.117065>. Furthermore, it provides plotting tools to visualize the results.

A collection of functions that perform operations on time-series accelerometer data, such as identify non-wear time, flag minutes that are part of an activity bout, and find the maximum 10-minute average count value. The functions are generally very flexible, allowing for a variety of algorithms to be implemented. Most of the functions are written in C++ for efficiency.