Implements the Exploratory Graph Analysis (EGA) framework for dimensionality
             and psychometric assessment. EGA estimates the number of dimensions in
	     	 psychological data using network estimation methods and community detection
             algorithms. A bootstrap method is provided to assess the stability of dimensions
	     	 and items. Fit is evaluated using the Entropy Fit family of indices. Unique 
             Variable Analysis evaluates the extent to which items are locally dependent (or
             redundant). Network loadings provide similar information to factor loadings and
	     	 can be used to compute network scores. A bootstrap and permutation approach are
             available to assess configural and metric invariance. Hierarchical structures
             can be detected using Hierarchical EGA. Time series and intensive longitudinal 
	     	 data can be analyzed using Dynamic EGA, supporting individual, group, and 
             population level assessments.

An easy-to-use implementation of the Engle-Granger
  two-step procedure for identifying pairs of cointegrated series.  It is
  geared towards the analysis of pairs of securities.  Summary and plot
  functions are provided, and the package is able to fetch closing prices of
  securities from Yahoo.  A variety of unit root tests are supported, and 
  an improved unit root test is included.

Miscellaneous functions to help customise 'ggplot2' objects. High-level functions are provided to post-process 'ggplot2' layouts and allow alignment between plot panels, as well as setting panel sizes to fixed values. Other functions include a custom 'geom', and helper functions to enforce symmetric scales or add tags to facetted plots.

An implementation of Bayesian hierarchical models
    for faecal egg count data to assess anthelmintic
    efficacy. Bayesian inference is done via MCMC sampling using 'Stan' <https://mc-stan.org/>.

Fits a variety of hidden Markov models, structured
	in an extended generalized linear model framework.  See
	T. Rolf Turner, Murray A. Cameron, and Peter J. Thomson
	(1998) <doi:10.2307/3315677>, and
	Rolf Turner (2008) <doi:10.1016/j.csda.2008.01.029>
	and the references cited therein.