Implements a method of iteratively collapsing the rows of a
    contingency table, two at a time, by selecting the pair of categories whose
    combination yields a new table with the smallest loss of chi-squared, as
    described by Greenacre, M.J. (1988) <doi:10.1007/BF01901670>. The result is
    compatible with the class of object returned by the 'stats' package's
    hclust() function and can be used similarly (plotted as a dendrogram,
    cut, etc.). Additional functions are provided for automatic cutting and
    diagnostic plotting.

These Bayesian models written in the 'Stan' probabilistic language can be used to interpret green crab trapping and environmental DNA monitoring data, either independently or jointly. Detailed model information is found in Keller (2022) <doi:10.1002/eap.2561>.

Tools and methods to apply the model Geospatial Regression Equation
    for European Nutrient losses (GREEN); 
    Grizzetti et al. (2005) <doi:10.1016/j.jhydrol.2004.07.036>; 
    Grizzetti et al. (2008);
    Grizzetti et al. (2012) <doi:10.1111/j.1365-2486.2011.02576.x>; 
    Grizzetti et al. (2021) <doi:10.1016/j.gloenvcha.2021.102281>.

Methods for manipulating regression models and for describing these in a style adapted for medical journals.
  Contains functions for generating an HTML table with crude and adjusted estimates, plotting hazard ratio, plotting model
  estimates and confidence intervals using forest plots, extending this to comparing multiple models in a single forest plots.
  In addition to the descriptive methods, there are functions for the robust covariance matrix provided by the 'sandwich'
  package, a function for adding non-linearities to a model, and a wrapper around the 'Epi' package's Lexis() functions for
  time-splitting a dataset when modeling non-proportional hazards in Cox regressions.

Computes Gregory weights for a given number nodes and function order. Anthony Ralston and Philip Rabinowitz (2001) <ISBN:9780486414546>.

Functions which make using the Generalized Regression Estimator(GREG)
    J.N.K. Rao, Isabel Molina, (2015) <doi:10.3390/f11020244> 
    and the Generalized Regression Estimator Operating on Resolutions of Y (GREGORY) easier. 
    The functions are designed to work well within a forestry context, and estimate multiple 
    estimation units at once. Compared to other survey estimation packages, this function has greater flexibility when 
    describing the linear model.